The current economic environment is a good time to be picking up patents at pennies to the dollar either directly from inventors or smaller companies for quickly enhancing the existing patent portfolio and thereby increasing your counter-sue threat to anyone who may sue you for infringement.

One of the popular techniques is Quantitative Portfolio Gap analysis that is used to identify weak areas in a patent portfolio that may benefit from such a strategy.

An important pre-requisite for such an analysis is having a set of technology categories around which your business revolves. These categories bring business sense to your analysis and so how you structure them will have a direct impact on your strategy.  More and more organizations have and maintain a set of well-defined categories around which their products and businesses revolve.

To begin to understand where you have quantitative gaps that can be filled up, a smart way is to categorize the entire prior art that exists in your field along your categories. Although having to categorize competitors portfolios may appear as a daunting task, various text mining and portfolio categorization tools can help accelerate your process. The next step is to compare your portfolio with the key competitors. By comparing the different portfolios quantitatively and you are essentially trying to locate areas where your portfolio is significantly smaller than the competition.

Once you have identified the areas, remove your and key competitors patents from the set and focus on the remaining patents in the category. It’s important to update the Patent Assignment information from the US Assignments database so that you are clear about the current ownership of the patents. Again patent analysis tools can help make this task much easier. Post this, look out for the following:

• The bottom 20-30% of the Assignees
• One year only Assignees – Companies whose patent(s) fall in just one year implying that their interest is perhaps opportunistic and not part of any continuous research or product development
• Old Assignees – Companies whose patents fall only in the earlier years and which do not have any new records say in the last 5 years implying that they aren’t focused any more in this area
• Universities and Individual Inventors

Patents of interest must be checked for legal validity to filter out those that haven’t expired. For those that have recently expired due to failure to pay maintenance fees make sure you check if they fall under the revival window since such patents can be easily picked up. Finally, you can leverage the services of an IP broker who will help hide your identity while finding if the other party is interested to sell and will further help in structuring the transaction.

        

My previous blogpost (Corporate IP Practitioner's need for flexibility and transparency ) had mentioned that a combination of a patent analysis platform such as Patent iNSIGHT Pro with a patent database can make a powerful and yet cost-effective solution to your needs for flexibility and transparency while accelerating activities that usually eat up most of your time. Let me elaborate on that here.

With the current downturn in economy, chances are that you would be dealing with IP or R&D budgets cuts and your key concern today is to ensure that Intellectual Property research and analytics activities continue to deliver greater value to the management, the R&D and Licensing/Business Development while addressing the increasing needs posted by M&A, Litigation and Open innovation during these cuts.

Due to the variety of Intellectual Property research tools and databases in the market, its difficult to understand what tools would fit your need. Most experienced researchers say that since each tool has been designed from a different perspective, there isn’t one database or tool that can help address all your needs. So when trying to optimize your IP tools expenditure the question that arises is: Which tool or tools meet most of your needs ?

Now while your top-level analysis projects may be Infringement analysis, Freedom-to-Operate, White-Space & Gap Analysis, Portfolio mapping or Competitive Landscaping, they all boil down to unique IP procedural needs. Here is a quick IP research and analysis process need checklist that you can use to map out your needs:

1. When searching, I want to quickly search across a wide set of patent offices
2. I want to setup alerts on key interest areas, companies, classifications or inventors.
3. I want to organize my results according to folders of my choice and need full flexibility in grouping, filtering, categorizing the records
4. I want to generate highly flexible tabular and descriptive reports in Office documents such as Word and Excel so that I can customize them further
5. I want to size up the results quickly to understand key patent biblio. parameters such as Assignees, Inventors, IPC/UPC spread, citations and their trends across the years
6. I would like to keep one record per family for some analyses and treat all family members as individual records for other
7. I want to categorize technology result sets into my company’s internal categories and then use that for further trend analysis in combination with other parameters
8. I want to leverage text-mining tools such as clustering and fine-tune it to generate meaningful clusters/topic from the text of patents
9. I want to analyze not only at cluster/topic level but also at “Keyword” level so as not to miss out even a single technology term
10. I want to analyze related content such as legal status, family information, litigation history along with patent data
11. I want to generate customizable charts and graphs with ease and would prefer interactivity such as drilling down within a chart
12. I want to assign my own internal ratings (such as commercial importance, legal threat, technology relevance, business risk) to the patents and then use the for further mining and analyses
13. I want to leverage algorithmically pre- calculated metrics for a quick sizing up the portfolio. (E.g., of such metrics are Portfolio Age, Technology maturity, Citation index, Science index)
14. I want advanced interactive visualizations such as 2D landscapes, Heatmaps, Treemaps, Citation trees, Family trees and other newer ways to represent complex informational relationships
15. I want to combine external data such as financial information, commercial information, technologies-up-for-sale information in my analyses

 If you have checked more than four of the items above then your needs extend beyond patent searching, and you have three main options available in the market today:

Solution 1: An offline analysis solution (such as Patent iNSIGHT Pro) with capability to automatically integrate data from free online sources and commercial sources
Solution 2: An integrated analytics driven database
Solution 3: A database + offline analysis solution

Solution 1 - An Offline analysis solution

Pros: Flexibility, Comprehensiveness, Customizability, Cost Effective Cons: No alerts, Needs time to build your analysis portfolio, No pre-calculated metrics

This option is good if you do not require instant analytics results since preparing your analysis portfolio can take a couple of hours or more depending on the whether you are working on hundreds or thousands of patents. With such an analytic solution you may not have alerts since the analysis is conducted over your result set. As a result, this option meets 75-80% of the needs listed above.

Solution 2 - An integrated analytics driven Database

Pros: Quick Analytics; Pre-calculated metrics can be helpful on occasions (esp. for valuation studies) Cons: High Cost, Coverage may not be as good as a specialized searching database; Pre-calculated metrics can be highly objective and non-transparent, lesser flexibility for those who want to drive the analysis process as per their needs

The definite advantage here is being able to search and quickly view pre-calculated analytics over the search results. If you are looking for answers at a relatively broad level and especially if you are considering analytics towards portfolio valuation or rapid portfolio evaluation then this is an option worth considering. These solutions may loose out on the flexibility you need and on occasions you may have export values to Excel and then pivot out to the exact answer you want. As a result, this option again meets 75-80% of the needs listed above.

Solution 3 - A Database + Offline analysis solution

Pros: Quick Analytics, Cost Effective, Coverage, Flexibility, Comprehensiveness, Customizability Cons: Lesser number of Pre-calculated metrics

This option may not provide as many pre-calculated metrics but by using a specialized search database you capitalize upon extensive worldwide coverage and all the tools you need to build the right search set. You can then export these results quickly into an offline analysis tool for detailed and dully-flexible analysis. Some pre-calculated metrics may not be present but if you do not rely or require these then this option offers you the maximum amount of features and meets 90-95% of the needs listed above.

And finally the cost…
Per prevailing market rates for IP products and databases Option 1 can cost you between 2500-8000 USD depending upon product and its capabilities. Option 2 can start from 12000 USD and can go upto 50000 USD while option three gives you maximum capabilities and still costs you between 8000-12000 USD again depending upon the type of database and analysis tool.

To sum up, doing a thorough research on the possibilities and capabilities of different solutions and understanding their price-points can help you increase the depth, quality and efficiency of your IP operations and yet reduce your overall IP tools cost.

        

Corporate IP practitioners, both managers and analysts have IP needs that are different from external consultants and IP Analysis service providers.

Chances are if you are corporate IP practitioner, when you initiate IP research for a new product/technology area, mapping intellectual-property is just one aspect of analyzing IP and a lot of your day to day IP research work besides patent searching would involve:

• Creating different kind of Excel or Word summary reports that help communicate patent and journal information between the you, R&D and management
• Coordinating processes and material for rapid screening through of patents by the R&D team
• Analyzing and manipulating related content such as US Assignments information, Sequence Listings, patent families, legal status.
• Grouping and filtering patent and journal data based on different criterion and assigning a rating that can represent its importance from technology, legal or commercial standpoint
• Categorizing patent data according to technology or product groups defined within the organization and maintaining updated patents sets (Techfolios) for each group. (Critical insights are usually revealed when you analyze patent data in context of technology and business categories that are relevant to your company and so categorization (or buketization) is important.)
• Managing patent images and patent PDFs effectively along with patent data

So, one of the key aspects that you should consider when considering an IP solution is your need for flexibility with the data within the solution. Our experience has been that most corporate IP professionals cannot have enough of “flexibility” when it comes to patent data and usually work on the leading edge of what one can do with the data. Managing the overall process of reporting, screening, and analyzing requires a lot of flexibility in manipulating, categorizing, grouping and reporting patent data and this can significantly burden corporate IP managers.

Transparency in analysis is also very important. “I could get thrown out of my management meeting if I don’t have the exact logic to back the analysis output” says one user. Its important for your analysis solution to provide transparency at each stage of the process. Most advanced users for Patent iNSIGHT Pro have questioned our charts and visualizations or even algorithmically calculated fields and we have helped them understand the full logic behind each. While there isn’t any exact statistic I could locate, based on what most researchers say it appears that very few people base decisions on patent maps that aren’t backed by a full understanding of the logic (and in many cases screening of patent content) behind the map.

A combination of a patent analysis platform such as Patent iNSIGHT Pro with a patent database can make a powerful and yet cost-effective solution to your needs for flexibility and transparency while accelerating activities that usually eat up most of your time. Without the right set of tools you can be spending weeks in achieving what would otherwise take a few days or lesser.

        

As a technology driven company, your business either revolves around a core technology in case of a startup or around multiple technologies and products for a large corporation and chances are you would be already accessing patent information from a patent database. However, if you are serious about IP and its role in your technology strategy you need patent mining and technology landscaping over patents not just restricted to your company’s patent portfolio but over all patents related (both directly and indirectly) to technology space you are in.

The success of in-house patent mining activity largely depends on - what you analyze, how you analyze and how you communicate the analysis to those who need it. A fundamental activity that provides a base for all of this is having a well maintained technology portfolio. Lets call it a “techfolio”. Formally defined, a techfolio would be a constantly updated set of technology records- patents and journals stored in a platform which makes it easy to analyze them in many different ways when required.

How to create and maintain a techfolio? The overall process is not as difficult as it may appear. The steps to create and maintain a techfolio can be as simple as:

1. Start with a good patent and journal search
2. Integrate your results in a common analysis medium
3. Setup alerts on your search strategy and update your techfolio from time to time

Start with a good patent and journal search
Perform a state-of-the art search for the particular technology over patents and journals in the technology space. If you are an R&D professional without much exposure in patent searching, it is advisable to involve a professional searcher for this step.

Integrate your results in a common analysis medium
The analysis platform where you integrate your results plays an important else the process may become cumbersome and frustrating. Too often the underlying analysis and storage platform or medium is Microsoft Excel, raw SQL database or perhaps a generic text mining solution. Since these are not specifically designed to suit techniques for technology analysis, you either end up spending too much time writing Excel Macros, SQL queries and doing all those things which make you say “there has to be a better way!”. Generic text analysis solutions that do not understand patents and its special characteristics such as Priorities, Families, Claim structure, Legal Status and other unique bibliographic fields would perhaps do more harm than good.

Setup alerts on your search strategy and update your techfolio from time to time
Constantly updating a techfolio can become cumbersome and repetitive but solution providers can help you automate alert integration and thereby making it easy for you to keep the techfolio up-to-date.

A well maintained techfolio can save a lot of time by avoiding repeat search work for each internal project. You can mine (categorize, slice-n-dice) techfolios for different reasons at all stages of your product/technology development and commercialization and apply those insights for R&D strategy, licensing, M&A and business development.

        

The trend of keeping R&D professionals from being exposed to patent information on a need-only basis is reducing as companies realize that product innovation today requires more than just the strategy of applying innovative thinking.

Till date, popular reasons for having research teams to not look at patent data have been patents research can - bias the innovative-thinking of inventors, reduce possbility of a "willful infringement" being proven in the event there is a future infringement case and finally, result in increased number of prior art reported in new patent applications.

More and more senior R&D professionals such as Technology Managers and Product Heads are turning to patents to refine their R&D strategies. They want to make sure that the teams are not wasting research time re-inventing the wheel and if research is to hit a patent wall eventually then its better to research alternative approaches from day one. Open Innovation is also to be driving this shift as R&D teams collaborate with individual inventors, universities and research institutions and tap external IP for their products. They are inclined to buy (or license) a portfolio of strong patents available from such sources rather than invest into research and generate workaround approaches.
 
Doing so, allows companies to bring their products faster to market, reduces research dollar wastage, decreases risk of engineering failure and improves quality of new patent applications and overall patent portfolio.

For leveraging IP insights technology managers need more than just search results. They need to create portfolios (either by company or by technology) and analyze them. Patent analysis solutions play a significant role here for R&D Managers allowing them to:

• build competitor portfolios and analyze then for threats, gaps and to map their research directions
• build technology portfolio and mine them for trends, insights and white-spaces
• analyze citation sets for technology evolution, portfolio strength analysis or to locate who may be building up on their portfolios
• look into existing portfolio to identify redundancies and non-core sets

Product innovation requires closer integration of IP Strategy in day-to-day decision making. Decisions such as where to spend R&D dollars, which direction to take existing products into and what research areas to exit are core to any technology driven company and must have IP as one of the key considerations.

Patent analysis solutions such as Patent iNSIGHT Pro can help technology managers gain actionable insights from IP. We are seeing a growing adoption of the solution amongst senior R&D professionals and assume that the trend is reflective of the fact that day-to-day technology decisions are increasingly based on intelligence from patent data.

        

Amongst various analyses performed on patents, the area where specialized software helps immensely is text-mining and two of the most popular text mining techniques used over patent data are:
    - Text segmentation / Tokenization
    - Text Clustering / Topic identification

Text segmentation is a process of analyzing the patent text and identifying smaller meaningful segments from the text. These segments are also called as Tokens or keywords. Various analyses can be performed using these tokens; however for large patent sets the number of unique tokens can be very high thereby making it unsuitable for certain types of analyses.

Text clustering helps identify important topics or concepts (clusters) from a set of documents. Clustering of key patent data documents (such as Title, Abstract and Claims) has been used in various Patent Analysis tools and can help bring out the otherwise hidden insights within patents. Analyzing relationships between generated clusters or analyzing relationships between patent classifications and clusters are popular mechanisms used by researchers especially those in a competitive intelligence role.

Classical algorithms used for clustering are K-Means or Bayesian Naïve. Their output is a set of categories (single level or hierarchical), each of which contain a group of patents. The name of the category is usually derived from the text of the patent itself and can also be a combination of multiple terms. Usually advanced algorithms can understand parts-of-speech and merge names accordingly. For instance, “tip of the probe…”, “using a probe tip…”, “with a probe whose tip is used for…”, and “probing the substrate with the tip…” will be merged under “probe tip”.

Algorithms can also differ on their capability to cluster patent under single or multiple topics. For patents it is desirable to have algorithms that place a patent under more than one topic since an attempt make a best-match for the patent under a single topic may lead to errors in interpretation.

One of the key challenges of clustering algorithms has been to make the overall process transparent for IP Professionals who usually find it hard to accept results of “black-box” clustering engines. Newer clustering algorithms provide the analyst control over most aspects of the clustering process thereby allowing then to fine tune the clustering output and train the algorithm to deliver more relevant results. The analyst can also now specify how deep s/he wants to go and choose to highlight broader or finer (more specific) topics.

Another challenge has been to make it easy for the analyst to influence the choice of the terms being picked up such to avoid picking up meaningless terms or to give importance to a certain class of terms. Apart from just being able to ignore some words (stop-words) it is important to have the power to set advanced filters that decide the choice of the labels used to represent the topic. For instance these can be, whether to ignore or give more importance to - words in ALL Caps, words starting with or containing a number, words containing more than one hyphen (compound names) or just words that are too long or too short. Even a minor change using such filters can have a reasonable effect on the topics that are chosen.

To see patent text clustering in action on patent data and understand its benefits via a sample use case scenario please read the full article here.

        

White-spaces are gaps in a technology landscape that have potential for attaining exclusivity. Many Technology and IP managers today look at white-space analysis as one of the key methods for strategic product innovation. Using white-space analysis they:

• Refine research direction by finding new areas for innovation and exclusivity
• Enhance product-patent portfolio. Broaden scope of existing patents by locating spaces around your patent positions which should perhaps be included in your claim coverage

In Patent iNSIGHT Pro you can use a combination of user defined categories and co-ocurrency analysis to conduct detailed white space analysis.

To start with, you should be clear along which lines or dimensions you are looking for gaps. Such as - By Product, ByMarket, By Method of Use, by Capabilities or By Application or Business Area and define the exact categories within the dimension.

The white space analysis activity proceeds in five steps:

1. Conduct a broad search and create a set of patents

2. Generate keywords (terms/tokens) from the claims of patents. Use the stop-word customization and keyword generation feature to generate a comprehensive set of keywords from the claims of the patents.

3. Cleanup keywords and assignees using various tools in the software. The raw lists of keywords and Assignees can be cleaned using multiple tools such as Fuzzy matching or by applying a thesaurus.

4. Categorize (Bucket/Group) patents along the dimensions decided for the analysis. In Patent iNSIGHT Pro we call them user defined categories or UDC for short. Depending on the dimension the method of categorization will differ. For large sets of patents manual categorization will take a lot time and there are ways by which you can automate the process.

•  For instance if the dimension is more functional you can map the categories to the IPC/USPC classes and assign the patents in each class to the category. (Using Portfolio Cluster Engine in Patent iNSIGHT Pro)
•  As a second example, if categories can be distinguished by the use of a particular keyword in claims then you can use iterative Boolean searching to assign patents to their categories. (Using Advanced Boolean searching)

5. Look for gaps and patterns by generating the following analysis matrices:

• UDC vs IPC/USPC : Detect whether a particular classification which may represent a method of use or a class of compounds etc have not been applied to any of the categories you have defined.
  
• UDC vs Keywords : See what combinations of keywords have appeared in concordance with the categories. Keywords usually are a good choice since they comprehensively cover all terms, many of which you may not have thought of, and the absence of a relevant keyword in a related category is the early signs of a white-space. For instance if your dimension is by Method of Use, then such a matrix will highlight how different terms from the claims occur in various methods of Use.
   
• Keyword vs Keyword : For fine grained pattern and gap detection.

6. Finally, once a white-space is detected, you must conduct a targeted search across patent databases and undertake critical manual review of the patents around it to confirm the existence of a white-space.

        

I have been asked by many researchers on how an Excel pivot table is different from the co-occurrence matrix that we provide in Patent iNSIGHT Pro since both are primarily used to generate charts and trends between two or three analysis points.

While Efficiency, Ease-of-use, direct integration between unstructured and structures fields, are perhaps obvious reasons, I feel two key capabilities make Patent iNSIGHT Pro co-occurrence analyzer a lot more powerful for the end researcher:

1) Capability to Drill Down, quickly read-through and analyze patents behind the numbers in the matrix

Consider the sample matrix shown below:



When you are analyzing a matrix like the one above your first instinct is - What are the patents behind a particular cell? 

Researchers I speak to tell me that they would like to quickly jump to the Bibl. & abstract or Claims of patents behind a cell. This capability to quickly go through patents in context of an analyzed segment makes a big difference to the quality of interpretation made. In Patent iNSIGHT Pro all you need to do is right click and select “View records”.

2) Capability to create subsets from the matrix and slice the subset further by a different dimension

Lets say if your question was “In a particular space, which companies were most active at the peak of the technology lifecycle and at that time what countries did they focus on for protecting their inventions?”

For this, one would first look at the Assignee-Filing Year spread and see which year(s) saw the peak filing activity. Then only for those patents in the peak years, analyze the coverage (Assignee – Family Countries).

So what you intend to do is pick up a subset of patents from the results of one relationship and apply another relationship to the subset. In Patent iNSIGHT Pro you can select a couple of cells in the Assignee- Filing Year relationship, right-click to group the patents and then jump to the Assignee-Family Coverage relationship for the subgroup all within 4-5 clicks.  I will leave it to you on how one could achieve that in Excel.

In sum, if you think of it, both the capabilities appear as must-have if you think of a co-occurence matrix as a powerful analysis tool to manipulate, slice-dice and dig through the patent data and not just as a precursor to generating a chart.

        

For companies it is critical to detect white-spaces and patent minefields early in the R&D cycle each of which can perhaps generate or save millions of dollars at a later stage. Traditional graphs and charts are good for displaying the results of an analysis activity but not for quickening and improving the analysis process.

An increasingly used mechanism is visual analysis of patents that involves 2-Dimensional spatial patent visualization and leverages the capability of the human visual system to identify patterns and anomalies. The key advantages of visual patent analysis are that you can drastically reduce the time-to-insights and explore IP-congested technology spaces in a swift but efficient fashion.

The ease of use and intuitive nature of visual analysis tools makes it easy for even business and R&D teams to use for their analysis needs. (Usually in organizations, the R&D, the patent information team, the legal team, the marketing cum business strategy team and the licensing team are involved in various parts of the IP strategy driving a product.)

Other important benefits which visual patent analysis provides:

• Ease of navigation across relationships- Can be used for exploring through networks of relationship between companies, inventors and their research or you can also explore semantic relationships between patent content.
   
• Quick interpretation - 2-Dimensional spatial mapping of technology clusters remains as one of most comprehensible ways to represent a landscape and can be easily interpreted
   
• The Peripheral vision advantage – You can benefit from being cognizant of the clusters around your focus area. In some case these “peripheral clusters” may contain the golden nugget you seek.
   
• Powerful highlighting, search and dissection tools combined with a rich intuitive display makes is easy to detect patterns and irregularities within the patent landscape. Such capabilities make the visualization many times more powerful. For instance Google Maps would’t be as powerful without it’s built in geographical search, highlighting and other navigational options.
   
• Clusters that are co-located based on semantic similarity are very useful when conducting infringement analysis. (Ofcourse, visual analysis tools must allow for clusters to be generated specifically from the claims section for undertaking infringement analysis)

To sum up, visual analysis is a powerful method to address challenges posed by patent information overload.

        

As an Intellectual Property Professional, it is important that your strategy is clear before the patent drafter begins to write the claims. There are many claims construction approaches to attaining exclusivity for your innovation either by a broad claim, a series of narrow claims or a combination of both. While your exact strategy makes a lot of difference to the way claims are constructed, an important consideration is the choice of words.

The choice of words that you make will aid not only in patentability of the applications but also, at a later stage, in freedom-to-operate and infringement. Experienced drafters know that it is important to avoid commonly used words in the domain of the invention.

One way that you can prepare a claims wording strategy is to create a set of closest prior art and using a text mining software, segment (tokenize) the claims. In case of patent drafting, it is best that you do not apply any taxonomy or thesaurus to fuse generated segments (or keywords) since you would like to see all popular variations.
 

For organizations, its advantageous to view these statistics in context of other companies in the same domain (using a Assignee-Keyword matrix). Interpretation made from these matrixes can help not only in the choice of words but also in your overall patenting strategy for your product.

For instance I segmented the claims and created a similar matrix in a search set for a drug (citalopram) in Patent iNSIGHT Pro Co-occurance Analyzer and exported that into a Patent Assignee-Keyword Matrix in Excel. While many different interpretations can be made from such a matrix, if your interest is to work around key claims then the spread of assignees around the keywords can greatly help your choice of words for the claims.

The matrix also helps in competitive intelligence. For instance a look at all the claim segments containing the words "disorder", "phobia" or "syndrome" gives a clear indication of the applications areas that are being targeted by the companies.

So, while technology landscaping requires clustering the keyword segments into topics using various clustering algorithms, claims keyword analysis has many advantages for creating a patenting strategy.