Patent Landscape Report on Blockchain by PatSeer Pro

Using Patseer to Search & Analyze Patents on Blockchain


This patent landscape report on Blockchain takes a look at the Intellectual property trends and filings being done by companies and institutions active in this technology area. All charts and analysis in this report have been prepared using PatSeer Pro.

This report analyzes research trends of blockchain with a focus on Constructive Technologies, Common Standards, Protocols, Cryptographic Methods and Applications.

To read the complete analysis visit:  Patent Landscape Report on Blockchain by PatSeer Pro

Filing Trends

The chart below shows number of filings for Blockchain during the last 10 years. Trend analysis based on filing of priority application indicates a gradual increase in number of applications being filed. Maximum number of patent applications (191) taking/having priority were filed during 2014.

A sudden rise in patent filing activity in the domain of blockchain during years 2013-14 indicates widespread interest in the given technology domain.

It’s clear the current activity around these technologies is likely to continue seeing more innovation in the near future.


PatSeer Search Recall TM feature

Top Companies

The chart below represents top companies active in blockchain technology, with a single representation from each family.


PatSeer Search Recall TM feature


Research activity around the world

The below map represents the geographical filing relating to Blockchain. The map helps provide an indication of where innovation in this area is originating.

United States is the leading country in this field with 409 families followed by China (251) and Korea (120). The strength of the coloring represents the proportion of patent applications

Research Activity around the world Blockchain


Technology Landscape for Blockchain

The patent landscape map below represents key concepts for different companies across generated across title, abstract and claims. Themes are collection of prominent topics extracted from the patent data and grouped under relevant parent tags.

Clusters for Signature, Public Key, Private Key and Card Purchase Structure are close to each other as there is high degree of relevance between the records present in those types of methods


Report Includes

  • Correlation Map for top companies across different Themes
  • Inventor groups of key companies in Blockchain
  • Citations for Bitcoin
  • Key Company Analysis
  • Key Companies activity across Applications
  • Key Companies activity across Common Standards
  • Summary

To download the report in pdf format :Email Us


Patent Landscape Report on Biochips


This blog categorizes and graphically analyzes biochips from various perspectives such as the fabrication techniques, methods involved, biochip types and applications and highlights the key companies involved.

IP Analysis

This Patent Landscape/Analysis Report on Biochips will showcase the publication trend,  top companies, research activity around the world, company activity across application, biochip types vs methods, technology landscape for methods and much more can be found on Patent iNSIGHT Pro website reports section.

Publication Trend

What has been the publication trend for biochips?

Innovation around biochips and resulting patent publications started to show up from 1986 with a spike in 2002. It’s clear the current activity around these technologies is likely to continue seeing more innovation in the near future.

Patent Publication Trend for Biochips

Top Companies

Top Companies researching in Biochip

The top companies in biochips are:



The complete Assignee table is available in the Excel file here.

Research activity around the world

The table below ranks top priority countries and helps provide an indication of where innovation in this area is originating. It shows perfect indication of where innovation is taking place. It can be seen China has 1201 filings (INPADOC Families) followed by US and Korea with 629 and 565 filings respectively. The strength of the colouring represents the proportion of patent publications.

ResearchActivityAround The world for Biochips

Company activity across Applications

  • The chart below shows research activity of companies across different applications
  • Merck leads the research around Biomarkers and Organic Semiconductors
  • Rosetta Genomics leads the research for diagnosis of cancer using biochips, it also leads the record count for Hybridization
  • Nucleotides and Gene Diagnosis are the application areas wherein most of the companies are present

Company activity across Applications for Biochips

Biochip – Types vs Methods

In the map, different types and methods are connected through links whose thickness and color intensity is directly proportional to the number of records relating them. The number (in red) next to each line represents the number of records present in the respective category. It can be that Gene Expression and Electrophoresis are the methods where DNA chips are used the most.

Also, ELISA followed by Gene Expression is more often used by Protein Chip for diagnostic purposes. Similarly, Thin Layer Chromatography and Magnetism are exclusive to Protein Chip and DNA Chip.

Biochip Types vs Methods


Technology Landscape for Methods

The contour map below represents key concepts for different companies across various methods where biochips are used.

Clusters for Internal Radioimmunoassay, Immunohistochemical and Immunofluorescence are close to each other as there is high degree of relevance between the records present in those types of methods. The patents represented by dots were coloured by company.

Contour Map for Biochips
The entire report is available for download here: Patent Landscaping – Biochips



Patent Landscape Report on Shape Memory Material – Polymer and Alloy


This blog takes a look into the patenting activity around shape memory material uncovering the companies, inventors, and key applications.

A shape-memory alloy (SMA, smart metal, memory metal, memory alloy, muscle wire, smart alloy) is an alloy that “remembers” its original shape and that when deformed returns to its pre-deformed shape when heated. Similarly shape-memory polymers (SMPs) are polymeric smart materials that have the ability to return from a deformed state (temporary shape) to their original (permanent) shape induced by an external stimulus (trigger), such as temperature change.

IP Analysis

IP analysis in this blog will showcase the publication trend, top companies, research activity around the world, and company activities across Polymer & Alloy, company activities across application and Technology Patent Landscape. Detail IP analysis such as key statistics of companies and inventor, Trends US, DE, GB, JP and FR and much more can be found on Patent iNSIGHT Pro website reports section.

Publication Trend

What has been the publication trend for Shape Memory Alloys?

 Innovation around shape memory alloys and its resulting patent publications started to show up from the 1990s with a spike in 2004. But the real surge in the activity around this technology happens in last 5 years. It’s clear the current activity around these technologies is likely to continue seeing more innovation in the near future.


Top Companies

The top companies in shape memory alloy are:




The complete Assignee table is available here 

Research Activity around the World

The table below ranks top priority countries and helps provide an indication of where innovation in this area is originating. It can be seen US has 4039 filings (INPADOC Families) followed by Germany and Japan with 535 and 456 filings respectively. The strength of the colouring represents the proportion of patent publications.

Research activity around the world for shape memory material

 Company Activity around Polymer 

  • The chart below shows research activity of companies across different types of polymers
  • Boston Scientific has the most number of records in Polyurethane Films and PET
  • Medtronic leads the research around thermoplastics and has research interest in almost all the polymer

Polymer Vs Assignees

Company activity across Alloys

  • The chart below shows research activity of companies across different alloys
  • Advanced Cardiovascular  is most active in Tantalum
  • Boston Scientific leads in research interest in Nitinol, Stainless Steel and Tungsten

Aloy Vs Assignee

Company activity across Applications

  • The chart below shows research activity of companies across different applications
  • Stent  is the most researched application area and is focused by most of the companies
  • Johnson & Johnson leads the record count for surgical fixation and prosthesis

Siemens is the only company focusing on aviation applications of shape memory alloys

Applications Vs Assignees

Technology Landscape

  • The contour map below represents key concepts across automation (engine cooling, driving mechanism, Internal combustion engines) and medical industries (lasers, surgical instruments and catheter devices)
  • The patents represented by dots were coloured by company
  • Clusters for Daimler which relate to Internal Combustion Engine, engine block and engine cooling are close to each other as there is high degree of relevance between the records present in those technology areas
  • Medtronic focuses mainly on medical devices and surgical instruments

Automation Landscape


The entire report is available for download here: Patent Landscaping – Shape Memory



Patent Landscaping – Gallium Nitride


This blog takes a look into the patenting activity around Gallium Nitride uncovering the companies, inventors, and key applications.

GaN is a binary III-V direct bandgap semiconductor commonly used in LEDs. Its wide-band gap of 3.4 eV affords its special properties for applications in optoelectronic, high-power and high-frequency devices. Because GaN offers very high breakdown voltages, high electron mobility, and saturation velocity it is also an ideal candidate for high-power and high-temperature microwave applications like RF power amplifiers at microwave frequencies and high-voltage switching devices for power grids. Solutions that use GaN-based RF transistors are also replacing the magnetrons used in microwave ovens.

Gallium Nitride (GaN) transistor models have evolved from GaAs (gallium arsenide) transistor models; however there are many advantages GaN offers:

  • Higher operating voltage (over 100-V breakdown)
  • Higher operating temperature (over 150°C channel temperature)
  • Higher power density (5 to 30 W/mm)
  • Durable and crack-resistant material

GaN devices are often grown on SiC (silicon carbide) substrates, but to achieve lower-cost GaN devices, they can be grown on sapphire and silicon wafers. GaN’s wide bandgap allows for higher breakdown voltages and operation at high temperatures. The high thermal conductivity of SiC makes it a better substrate than silicon for power amplifier applications that require good heat sinking.

Patent Search Strategy

Using PatSeer following search query was used to create patent set.


TAC– Title, Abstract, Claims

PBC– Publication Country

PBY – Publication Year

UC-US Classification

The query was directed to search through title, abstract and claims and was limited to US publications published during last 10 years. Result set of 7888 records with one publication per family (INPADOC Families) was generated and Imported in Patent iNSIGHT Pro.

IP Analysis

IP analysis will showcase the publication trend, Top companies,  activity around the world, Gallium Nitride – Application Areas vs. Crystal Structures, Landscape for Gallium Nitride applications and Analysis of significant companies within Gallium Nitride.

Publication Trend

The Bar chart is about Publication trend from last ten year.

It can be seen that publications for GaN are constantly rising from 2009 with the real surge in the activity around this technology has happened since 2012.It’s clear the current activity around these technologies is likely to continue seeing more innovation in the near future.


Image1_Pub Trend

Top Companies

The Bar chart deals with Top companies in the field.


Image2_Top Companies

Note: Records for Matsushita Electrical Ind Co Ltd have not been grouped with Panasonic Corp in spite of their merger with Panasonic, as some of the patents owned by both these companies have not been transferred to a single company.

Research activity around world

In terms of regional pockets where patent protection is being sought most frequently for these technologies, USleads the count, followed by the JPand KR.
The table below ranks top priority countries and helps provide an indication of where innovation in this area is originating:


Image3_Priority Country

Filing Trend of Patents across Top 15 US Classifications

The chart shows the spread of patenting activity across various subclasses of technologiescorresponding to US Class.

The brown trend line associated with US Class 257/76 {Active solid-state devices with -Specified Wide Band Gap (1.5ev)} shows an impressive spike from 2009 onwards. In the chart, it can be seen that US Class 257/76and 257/98 are most favored subclasses under which 1048 and 721 patents have been categorized respectively. These are followed by 257/13, 257/103, 438/478, 257/79 under which 628, 601, 526,467patents have been categorized respectively.


Image4_US Class Filing Trend_15

Company activity across Crystal Structures

The chart below shows research activity of companies across different crystal structures.

Univ California has research activity across all types of crystal structures.Intel and Corning focus only on Wurtzite.


Image5_Cos VS Crystal Structure_20

Company activity across Applications

The chart below shows research activity of companies across different applications.

Cree leads in research around high electron mobility transistors and defence with 82 and 28 records respectively. Samsung and Univ California are the only companies focusing on high resolution printing with 9 and 7 records respectively.


Image6_Cos VS Applications

Company activity across Physical Properties

The chart below shows research activity of companies across different physical properties.

Avogy focuses only in N-type.Panasonic leads in research across P-type. Sumitomo has fairly comparable portfolio across all the physical properties.


Image7_Cos VS PhyProp_20

Gallium Nitride – Application Areas vs. Crystal Structures

In the map, each structure is connected through links whose thickness and color intensity is directly proportional to the number of records relating them.

The number (in red) next to each line represents the number of records present in a particular crystal structure and application areas. It can be seen Wurtzite crystal structure is used in more number of applications as compared to other crystal structures. Aviation,Defenceand Satellite industry industries use onlyWurtzite and Zinc Blende crystal structures.


Image8_appln vs crystal

Note: Orange nodes represent the crystal structure, whereas purple nodes refer toapplication areas.

Landscape for Gallium Nitride applications

The contour map below represents key concepts for different applications of Gallium Nitridewith respect to complete patent portfolio.

Clusters for photo diode and photo detector appearcloser to each other as they share high contextual and conceptual similarity between them. The nodes were coloured by companies.

Image9_Application key text

The entire report is available for download here: Patent Landscaping – Gallium Nitride

image 6

Patent Landscaping -3D printing

3D printing or additive manufacturing is a process of making three dimensional solid objects of any shape from an existing digital model.  The additive process of 3D printing indicates successive layers of material laid upon each other to form the desired shape. 3D printing is quite a refreshing change from the traditional machining technique which relies mostly on removal of material by cutting or drilling, also known as the subtractive process.

The term additive manufacturing refers to the technology that creates objects through sequential layering. The 3D printing technology is used for both prototyping and distributed manufacturing with applications in architecture, construction (AEC), industrial design, automotive, aerospace, military, engineering, civil engineering, dental and medical industries, biotech (human tissue replacement),fashion, footwear, jewellery, eye wear, education, geographic information systems, food, and many other fields.

PatSeer Strategy:

 PatSeer which is smartly designed to sort, filter, create and analyze reports can be used to create queries to search and obtain records with respect to 3D printing. The following search query was created to sort 3D printing across various segments.

1)      TAC: Title, Abstract, Claims

2)      TACD: Title, Abstract, Claims, Description

3)      IC: International class

4)     CPC: Cooperative Patent Classification



[Figure 1]

These queries are directed to search through Title, abstracts and claims. The individuals are then collapsed into one publication per family which is then exported from PatSeer and then imported to Patent iNSIGHT Pro.

In the search query shown in ( Fig 1 ), result set of 2863 records were imported into the software.

False Positives:

 After the result sets were obtained, the few discrepancies such as unwanted and confusing terms were eliminated to arrive at a result set of 2635 records which formed the base for further analysis.

The elimination process involved removing all files with filling dates before 1990; irrelevant words like 3D colours and printing of 3D images were removed to create a very relevant and acute database.

Patent categorization:

 To analyze patents under 3D printing they are categorized under 3 broader categories mostly by technology, by material and by industry as shown in the image below.


[Figure 2]

Publication Trends:

What was the publication trend in 3D printing?

Once the patents were populated in Patent iNSIGHT Pro, the publication trend chart was generated on a single click using the dashboard tool. Innovation in 3D printing and its resulting patent publications started to show up from the 1990s with the real surge in the activity around this technology happening in the last 5 years. It’s clear the current activity around these technologies is likely to continue seeing more innovation in the near future.

The trends can be pictorially depicted in the image given below:

image 3

[Figure 3]

Top Companies in 3D printing:

 The following methodology was adopted to determine the leading names in the domain of 3D printing. Once the patents were populated in Patent iNSIGHT Pro, the assignee clean- up tools were used to normalize the names. Different cleanup tools were leveraged:

• To locate assignees for unassigned records

• To clean up records having multiple assignees

• To locate the correct assignee names for US records using the US assignments database

• To merge assignees that resulted from a merger or acquisition or name change.

 The dashboard tool within Patent iNSIGHT Pro was used to find the top 20 assignees within the given patent set. A visual graph was created based on the results of the top assignees with the number of patents alongside each one.



[Figure 4]

Company activities across technology:


1) The chart below shows research activity of companies across different technologies

2) Stratasys being the pioneers in Fused Deposition Modelling (FDM) have the highest

number of records in FDM

3) Materialise also has a large research portfolio in FDM


image 5

[Figure 5]

How was the result obtained?

 First various technologies were identified by manual research. Then by using a combination of semantic analysis tools such as clustering tools and searching tools available in Patent iNSIGHT Pro, records were categorized under different technologies. A co-occurrence matrix was generated using the co-occurrence analyzer to map the different technologies with assignees. The matrix was filtered for the top 15 assignees and was converted into bubble chart using the option provided in software for the same.

Landscape for technologies used for 3D printing

A patent landscape analysis will helps in gaining an overview of a technology sector, competitors and chronological developments in a particular field of technology.

In addition, it can also help you to better evaluate the economic value of a patent portfolio.

A patent landscape analysis helps in identifying the following:

  • The current trends in focus of companies, industries and countries
  • Technology leaders and their IP strategies and their business decisions
  • Technological positioning of companies and their chronological changes
  • Unique selling points of companies
  • Strengths and weaknesses of patent portfolios

The contour map below represents different materials used for the production of 3D objects with respect to complete patent portfolio. Clusters for Stereolithography and photolithography are close to each other as there is high degree of relevance between the records present in those technology areas. The patents represented by dots were coloured by company.

image 6

[Figure 6]

The VizMAP tool of patent iNSIGHT Pro is used for this purpose. First the clusters for different materials were loaded on the map. They were analyzed on basis of their contextual similarity using title, abstract and claims as Text and technology as UDC from the ‘Context mode’ option. We removed unrelated patents using the “Hide Unrelated records” option and one patent assignee using the options available in VizMAP.

The detailed report on patent landscaping can be downloaded from here : Patent Landscaping – 3D printing download

Slideshare presentation can be obtained here : Patent Landscaping Slideshare.



Methods for Assignee Normalization

Normalization is the process of efficiently organizing data in to eliminate redundancies.  In patent analysis, Assignee Normalization is a process of preparing clean and accurate Assignee names from the raw data that exists on the published record.  When assignees are not present or organized properly, the accuracy of the analysis is greatly hampered and the results cannot be relied upon. 
Let’s summarize the different challenges users face with respect to Assignees when working with patent data. These are: 
  • Unknown Assignees where there isn’t a Assignee name in the publication
  • Unclean Assignee Names (Misspelt or subsidiaries with different company endings)
  • Mergers and Acquisitions of companies
  • Multiple Assignees (or Inventor names appearing in the Assignee field)
The methods used to tackle each of the above challenges are different and there isn’t one size fits all approach possible. In this blog, we will take a look some of these methods.
Unknown Assignees
There are different methods used to locate probable assignees for records that don’t have one. This aspect is seen in US patent applications that do not have an assignee name until right before grant (mostly because companies don’t want to reveal their identities until the last moment). A user can use the following methods for locating probable Assignee for such records:
  • Locate assignee from INPADOC family information – The INPADOC database provides information of corresponding patent applications in different countries and these may include the assignee name.
  • Locate assignee using Inventor matching – The same inventors may have appeared in patents that have an assignee name. Further if the attorney too is same and/or the filing is around the same time, then one can assume with confidence that the Assignee for the unknown record will be the same.
  • Locate assignee from US Assignments Database (Only for US records) –  US applications may have already had an assignment event at the PTO which would be available from the Assignments database and this would make it easy to lookup the Assignee.
Finally if none of the above work, the user can either manually provide an Assignee name to the record or instruct the software to use the inventor name as Assignee name. Patent iNSIGHT Pro has automated tools for each of the above method that leverage the above logic used and provide Assignee suggestions to the user.
Unclean Assignee Names
Auto cleanup is used to combine large group of assignee and to create small groups which can be used for further analysis. This process is faster and mostly precise as compared to manual process. This activity can be performed by fuzzy matching, thesaurus matching and regular expression based pattern matching. 
Unclean assignee names may be in the form of misspellings of assignee names or subtle differences in naming of a company, occurrences of duplicate entries, no unique assignee records.
Fuzzy algorithm based merging of names might not be effective in cases where names are very short of when names phonetically sound similar (Short Chinese names). For this, we can use manual cleanup, wherein you can create groups manually. In Patent iNSIGHT Pro, a list of all unique assignees present in the patent data set is provided and then the user can choose any one of the above method to merge name. As seen in the figure below, it is evident that the selected set of assignees is the same organization.

Mergers and Acquisitions
In case of US records, for companies to be able to take action on any patent, they must report their ownership to the USPTO as per section37 CFR 3.73 . This information is publicly available in the US Assignment database and is highly valuable resource to track ownership. So if a user wants to find updated ownership information such as change of name, mergers, execution date, assignments database helps in tracking. Patent iNSIGHT Pro integrates with the latest Assignment data and gives current owner suggestions for all US patents and applications.

Multiple Assignees
Instead of having multiple assignee names, for simpler and precise analysis, a single assignee per document is useful. In many cases especially for WO applications, inventor names that as present as co-applicants may show up in the Assignee field and so it’s important to be able to remove these. Patent iNSIGHT Pro has automated tools to identify inventor names in the Assignee field and remove them. The alternative for the user is to manually go through the names which take a lot of time for large datasets.

Using Thesaurus for Categorization

In Patent iNSIGHT Pro the standard thesaurus option allows you to maintain term taxonomies and Assignee groups. Mostly you would be using this for cleanup activities. However recently at a client group meet, I was asked if it was possible to store complex search queries as synonyms for a technology term and manage them in Thesaurus type files.

Before describing how, I will quickly explain the need. Most users create multiple UDC (User Defined Categories) sets as custom data points to map/analyze a patent set. Categories can be – By Functionality, By Ingredient, By Product, By Technology-specific class etc. To begin with a user creates the category schema and then using Advanced Search, performs complex searches within the report and pushes the resulting patents into each category. So it appears logical to save the searches done along with the category name in fashion similar to a thesaurus. This is helpful not just for automation but also to allow for future use in a different report.

So lets get to how we can do this. There is an option introduced last year called Create UDC from Excel, which allows you to prepare these categories-search mappings and store them in Excel files. These files are like Thesauruses that you can manage and extend over time.

For example, let’s take the Fuel Additives technology space. There was a report we did on this that is available here.

A portion of the categorization from the report is shown below:

Say we wanted to have a thesaurus for the Fuel Additive categories listed under “Types”. A Sample Excel Thesaurus for this shown below:

Note: I have shown only some of the categories under Types.

In the excel sheet notice that search strings are treated as synonyms and separated by a comma. By default, each string is assumed to be searched against full-text but if you want to restrict it to a portion then you can do so as shown for Lubricants above. Also for Lubricants you can see that, synonyms may not be a text term and can also be an IPC code (or USPC/ECLA) too.

The comma can be replaced with an OR operator to create a single search string without affecting results. Although managing different shorter strings as synonyms separated by a comma is easier to interpret and resembles a thesaurus.

The Excel file can be passed to the Create UDC from Excel feature and at the preview stage you can even drag-drop the category to create a hierarchy.

The synonyms (aka search strings) are searched in the text of patents and the results are pushed into corresponding categories.

So the excel file like the one shown above works like a thesaurus which you can prepare and maintain for your technology categorization purposes. It is also more flexible than a typical thesaurus since:

  • you can combine non-text portions such as Classification codes
  • you can use proximity operators within words
  • you can force some words to be searched only in claims and some other in full-text within the same synonym group
  • you can include ignore words by using NOT operator

The last point is pretty useful. For example a thesaurus entry for Antivirus (in biochemical field) can be:

Antivirus (Antivirus not w/5 (computer or network or internet)),

(Anti-virus not w/5 (computer or network or internet)),

(Protease w/2 inhibitor*),


Doesn’t this seem like the obvious thing to do if you want to save and automate the process of categorizing records for use in other reports?

Overview and use of Correlation Maps

We recently introduced a new method to display network mode maps in VizMAP and this blog focuses on discussing details of this map.

First, a recap on network mode maps.  Let us look at a very simple table of 5 companies vs IPC Main classes on a random sample of patents an applications on antivirus. The data in the tabular format is shown below.


If we represent that in network mode of VizMAP it appears as:


Key IPCs in the map are automatically placed in the center and company portfolios are organized around the Assignee-IPC relationship. The patents (smaller dots) are colored by Assignee and shading demarcates individual company portfolios.

Clicking on HO4L IPC Node will highlight all records that fall under this category:

As you can see few records of each Company are classified under the H04L. Now we could also shade the portfolios by IPC but that would overlap with the existing companywise shading and make the map complicated. So if you wanted to quickly see a similar correlation between all IPC codes and all Assignees without having to click on each node? That’s where the correlation map comes in. The correlation map for the same data is shown below:



The map clearly shows how many records relate two nodes and the thickness of the line is also proportional to the number of correlating records. In addition to the data in the matrix the display also shows correlation between different IPC nodes. You can restrict the map to only the type of correlations you want to see and in the process bring out a visual that perhaps best represents the matrix data.

The correlation dosent need to be just Number of common records. We can have a co-citation map in the same display where the correlation is based on Number of common citing records. For example in the Fuel Additives patent set that we created for one of our Technology Insight Reports on Fuel Additives , a co-citation map for the Top-10 companies is shown below.


The map clearly shows that research on Fuel Additives happening at Chevron Corp and BASF AG is strongly related.

Focusing on core and managing research data efficiently during IP analysis

For IP professionals working in a patent law firm, a R&D driven company, research facility or even in a service provider, managing patent research process is plagued with inefficiencies.  With consumers of research information asking for faster turnaround times albeit with higher accuracies every professional must look into his/her research workflow and locate inefficiencies that are delaying the overall analysis process.
Based on our experience of working with researchers across a diverse set of organizations, we have split the overall activities performed by researchers into various core activities.
Core Activities Tools needed to speed up execution
Devising the search strategy Database to allow quick checking and refining of the search as the search made more precise.
Consolidating multiple searches into a common portfolio
Claims Analysis, Review and Rating, Narrowing down Generating Claims comparison charts
Claims Tree generation
Similarity search and tools to conduct advanced search (proximity/left-truncation etc) on claims
Tagging or scoring tools to mark important records as you come across them
Independent Claims exporting
Different patent text export formats including export of face pages for rapid review and scanning in a team environment
Categorizing and bucketing records Auto-Categorization to discover unique concepts and clusters present in the set
Tools to easily and efficiently create buckets and bucketise patents as you review them
Advanced search tools to dig through the data efficiently
Generating  charts, comparisons and dashboards that capture the insight you want to give Grouping and efficient slice-dice tools to accelerate the analysis process
Efficient matrix generators that allows you to compare 2, 3 or more properties at a time
Automated charting tools to convert filtered data quickly into a chart
Ready to use dashboards that allow you to gain insights and generate common analysis charts quickly
An IP research and analysis solution  can provide  IP professionals, tools to leverage at each stage of core activity execution so that they can focus on core activities without getting slowed down by procedures.
Working with IP data is characterized by working with a large input data sources and a large number of output data sources. To carry out what should be a well-researched analysis in a technology space would involve a patent database, several patent documents, patent text files, spreadsheets, working files, charts and reports. A lot of this becomes overwhelming when working only with spreadsheets. For example, the outputs alone would involve working with several spreadsheets let alone the spreadsheets which actually hold the source information and the working / analysis.  There are just too many files and data sheets to work with in different places and that’s often what makes the process difficult.
In addition to provision different analytic tools, an efficient analytics platform can also consolidate and organize these multiple files and data sheets into a single location so as to simplify management of the process.
Consolidation has been a key ingredient of the technology architecture of the Patent iNSIGHT Pro that also functions as an IP knowledge management software. From bringing together various patent databases and data sources to creating single view reporting dashboards for easy reviewing of outputs having all your data within reach from a single system alone improves the speed at which you can access IP intelligence.  It eliminates the need to navigate through several instances of Excel spreadsheets, various tabs with different data sources and multiple files across the desktop and allows you to manage everything through one interface. As a step torwards consolidating different analytics into a single view, the 360° series of reports one of the newer features on Patent iNSIGHT Pro for example, consolidates a number of report outputs into a single page dashboard view which is quicker and simpler to present and review as compared to a dozen output spreadsheet printouts which can take longer to comprehend.
If you find your IP research and associated information management process overwhelming with multiple files and data sheets across too many locations …consolidate! You will find things can become a lot quicker and far simpler.

Charge-Coupled Device – The Electronic Eye

Willard Boyle and George Smith are two innovators who just last week got the recognition they long deserved for their contribution which quite literally changed the way we see the world. The two Nobel laureates who were presented their Nobels for Physics in Norway last week invented the charge-coupled device which most of us commonly know as the CCD which is the core technology used by digital cameras today. What is fascinating is Boyle and Smith had invented the CCD 40 years ago back in 1969 and though all these years later as they collect what is perceived to be the highest accolade in science, perhaps the bigger prize was seeing how the finger nail sized device they came up with touched the lives of so many.

One of the largest impact it’s had is in the development of the digital photo camera which almost each of us own whether in the form of an SLR camera, a point and shoot digital camera or even one that’s housed in our mobile phones.  The core CCD technology is now being used in a variety of technologies and almost all electronic and appliances firms are involved in applications around it.

To see who is active and aggressive in CCD related research, we did a broad search on CCD technology and using Patent iNSIGHT Pro came up with a couple of quick stats. The first one is the overall trend across key Assignees that shows that while Samsung and Kodak have been periodically  filing for patents in this space, recent research has subsided for other large companies such as Hyundai, Fuji and Sony. One can easily see the emergence of Hon Hai precision Co as a recent company in this space.

To confirm this further, we split the company portfolios across 5 year sets (2000-2004) and (2005-2010) to compare their trends:

The above chart shows that big companies that have renewed interest in CCD and related technologies are Siemens, Honeywell, General Electric, Philips and Xerox. The activity analysis further shows some firms building targeted portfolios such as Hong Fu Jin Precision Co, Chemimage, Avision and ASML Holdings NV.

The trends of General Electric and Hon Hai Precision clearly stand out since both do not have any filings that talk about CCDs in 2000-2004 and have 16 and 68 filings respective in the last 5 years. To find out the focus areas of these filings, we used text clustering on the individual portfolios of each company. The analysis showed that the GE filings focus on Radiation detection, Scintillators, Plasma spectroscopy and X-rays. Hon Hai Precision Co’s focus was more on camera lens for imaging, monitoring and measuring across a variety of areas right from vehicular systems to cameras.

Finally, to know the different research areas in which CCD technology has grown into and their trends we took the IPC distribution again across a 5 year period and compares the growth/decay from 2000-2004 period to 2005-2010 period. This is shown below:

To sum up, forty years into the technology life-cycle, CCD is still going strong with companies across the world still discovering new applications in various areas with the help of this device.