IP & Patent Use Cases

Patents are essential to drive innovation and maintain a competitive edge through IP (intellectual property) management in many industries.

Clients in Intellectual Property & Patents and Life Sciences & Healthcare use the KMX Patent Analytics solution to derive contextual insights and knowledge from  mining complex and large datasources in patents and science literature.

The unique KMX Patent Analytics solution is leveraged in a wide range of industries including High Tech, Construction, Industrial Manufacturing, Chemical and Lifescience incl. Pharma and Bioscience. For these clients Treparel KMX has helped managing their IP value.

Different client cases KMX is implemented involves Patent Analytics (advanced search), Competitive Landscaping, IP Valuation, Drug discovery and Clinical Trials. For the specific high demanding needs of this group of clients, we have created an overview of various applications of the KMX platform. Note: this overview has no intention to be exhaustive nor complete.

Use Case 1: Improve Patent search process

Current (manual) patent searches take a substantial amount of time; business owner seeks to increase the efficiency/throughput of their searchers/IP department.

Goal: To increase the number of search-questions that can be performed and shorten the turnaround time (the time it takes to report results of search questions).

Source: Data is usually collected by search queries (e.g. from Derwent). KMX allows these queries to be broader, more general and include more documents. This happens outside of KMX.

How: By using KMX to quickly distinguish between relevant and irrelevant documents from a large set. The searcher specifies training documents for both relevant and non-relevant documents. Searchers no longer have to manually read the entire dataset but can use KMX to quickly and efficiently process large datasets and reduce the number of patents that need to be manually examined to a small subset (training data). KMX provides both the classification results as well as the ranked list of documents that, if desired, can be used to reduce the set of documents which are be to manually examined to a fraction of the original size of the dataset.

Benefits:

  • Turnaround time is reduced significantly
  • Precision and recall are industry leading, less risk
  • Searchers efficiency increases (can perform more searches in same amount of time)
  • Searchers can handle bigger datasets, datasets that manually would not be feasible, possibly able to answer new types of questions

Use case 2: R&D Planning support

Business owner requires information for R&D planning (and additionally wishes to increase the expertise of their searchers).

Goal: With KMX the searcher can examine an area of technology to gain a better understanding of the different classes present in the data to use this information to provide a R&D (planning) department with the information required to plan new research activities. Current patent searches are restricted to a number of patents that are still feasible for manual processing. As a result analyzing a patent landscape (with this we refer to all patents on a given (sub)area of technology, e.g. LED-lights) is a daunting if not impossible task due to the sheer amount of documents.

Source: Data can be collected by using broadly defined search queries or selections based on IPC (if the technology area is reasonably well-defined). This happens outside of KMX.

How: The searcher imports the data in KMX and uses the landscaping visualization to get a birds-eye view of the data. They can then use brushing to capture/highlight clusters, summarize the various topics and use the filtering function to remove documents that are not of interest. They can use individual document annotation to get a quick hint on the content of documents and use the full document view to examine a document more thoroughly. Using the landscaping visualization and the knowledge they gain from exploration, the user can capture the areas where R&D is lacking or even define new areas where research and development could be valuable.

Benefits:

  • Searcher can use the interactive visualizations of KMX to directly interact with the data
  • Able to quickly gain an understanding and overview of large datasets (datasets that would not be feasible for manual processing)
  • Use KMX visualizations and tools to report findings, highlighting classes and/or interesting sub-areas of technology
  • Provide R&D (planning) departments with the information they need Searcher can, in a more structural fashion, increase their expertise in an area of technology

Use case 3: Competitive landscape analysis

Business owner requires a competitor analysis for e.g. determining the product road-map, R&D planning, guiding the marketing department.

Goal: To map out competitors in an area of technology where the business operates. Information can be used for multiple tasks. E.g. marketing campaigns (distinguishing technology) to provide information to the various planning departments (new research directions), information for product managers etc.

Source: Data can be collected by using broadly defined search queries or selections based on IPC (if the technology area is reasonably well-defined). This happens outside of KMX.

How: The searcher imports the data in KMX and uses the landscaping visualization to get an overview of the data. The user can map the data on patent owner to a color-scale and highlight who has patents in what sub area in the area of technology. Additionally they can use brushing to capture/highlight competitor regions. Filtering of documents from competitors who have license agreements. They can use individual document annotation to get a quick hint on the content of documents and use the full document view to examine a document more thoroughly. Using the visualization and the various options to highlight, color, or filter the data to create communicative reports on the competitor activity and focuses in their business area of technology.

Benefits:

  • Use the interactive visualizations to gain a quick understanding of the competitor landscape and communicate these results
  • Provide various departments with a competitive analysis of the business area or new technology focuses
  • Provide strategic information on competitors with complementing technology for license deals

Use case 4: Reusing knowledge from multiple search activities

Business owner wants to retrain knowledge of previous analysis performed by the IP department and reapply it to new source data.

Goal: To reduce workload for similar future search questions by reusing a previous analysis.

Source: Data is usually collected by search queries (e.g. from Derwent). KMX allows these queries to be broader, more general and include more documents. This happens outside of KMX.

How: Keyword searches only results in a set of documents, these documents have not been evaluated by an expert. Although the query might be stored for future use, all the (new) results still require expert evaluation. This means that the expert has to manually read all new documents and evaluate them on class and/or relevance. Classification targets an area of interest, by storing the classifier and thus indirectly the knowledge the expert stored in that classifier (training data).

This classifier can be reused in a future similar search question to assign expert-defined classification labels and/or rank the results on relevance. Worst case scenario for classification would be to alter the training data to reflect changes or shifts in the technology area. Worst case scenario for query based results would be to manually re-evaluate ALL documents again. If a stored query is provided to a new/different searcher it does not relay anything but a result set that has to be evaluated entirely. A classifier provides a handhold on the results providing classification labels and/or a ranked list based on relevance.

Benefits:

  • Retain expert knowledge, captured in classifiers (even if expert leaves the company)
  • Share knowledge (in the form of classifiers) with co-workers
  • Increase turnaround time
  • Less redundancy in workload for searcher

Use case 5: Fast retrieval of specific patents

Business owner requires more information on a certain technology or patent.

Goal: Inform departments about a new relevant technology or patent or related technology.

Source: Data can be collected by using broadly defined search queries or selections based on IPC (if the technology area is reasonably well-defined). This happens outside of KMX.

How: The searcher imports the data into KMX and uses the landscaping visualization to get an overview of the data. The user can quickly find the patent (or a patent describing the technology) using filtering. The searcher can than scan neighboring documents and/or clusters to report about similar patents/technologies or related technologies. Or the searcher can define training data based on the patent landscape and use the classification technology to find more relevant patents.

Benefits:

  • Use clustering/classification as a more targeted search, query-based will bring a lot of noise
  • A more efficient quick means to research a certain patent/technology
  • Provide departments with relevant information in a faster more efficient manner

 

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