White Spot Analysis: The Potential of Patent Information ...€¦ · new product ideas and business...

White Spot Analysis: The Potential of Patent Information for Research and Development

Yvonne Siwczyk, Joachim Warschat Fraunhofer Institute for Industrial Engineering IAO, Innovation and Technology Management, Stuttgart, Germany

Abstract--Patents do not only offer legal protection, but also

provide an extensive source of technical information: pre-processed in “technology maps” or “patent maps”, interesting technical details can be identified for the own development of new product ideas and business opportunities.

The White Spot Analysis presented in this paper is based on a special patent map: building a problem solution matrix of patent data within a defined technology field, gaps – so called White Spots – can be identified, which lead to new business opportunities not described through patents yet.

The manual analysis of numerous patents is very time consuming and thus very expensive. The approach presented in this paper utilizes a text mining based method in order to support the extraction of problems and solutions from patent text. For the purpose of identifying only White Spots with a high economic attractiveness, a special assessment method is combined with the patent data analysis process.

The detailed process steps of the White Spot Analysis will be shown by a practical example regarding Electric Mobility, especially battery management systems for electric and hybrid cars.

I. RELEVANCE OF PATENTS WITHIN THE TECHNOLOGY MANAGEMENT PROCESS

Patent information has an increasing value for companies

during the whole technology management process starting from technology creation up to technology usage [9]. Thus for a variety of strategic business decisions patent data analyses can be necessary [3] [19]. Especially during the technology creation process patent information can be a very valuable basis for the development of new technologies and product ideas [5]. One common method of using patents as a basis for this development of new technical interesting ideas is TRIZ (Theory of Inventive Problem Solving) [1]. The method TRIZ is based on the identification of essential problems and solutions described in patents as well as the usage of the 40 problem-solving-principles that were identified by the inventor Altschuller [21]. Those essential principles are used for solving technical problems by using a systematic approach. So TRIZ takes advantage of the fact, every patent generally contains at least one technical problem as well as its associated solution. But not only when using TRIZ this detailed technical information can be used as input for finding the answers to own technical questions during the technology creation process. There are various methods of analyzing patents that in some cases also include bibliographic data like for example the patent assignee, application date or the International Patent Classification (IPC) number. Bibliographic data is generally used for

example for the analysis of competitors as well as the opportunity to identify technology and market trends [6].

All types of patent data analyses have in common that in a technology field hundreds or even thousands of patents must be read and analyzed in order to extract the relevant information. This is a very complex and time consuming process, if there is no software assistance. Therefore following chapter addresses the existing software solutions for patent data analysis. II. STATE OF THE ART IN PATENT DATA ANALYSIS

In recent years a variety of software solutions have been developed for different applications, ranging from special patent search tools to complex patent analysis tools providing for example patent mapping features [7] [10].

Most of these patent analysis tools generally offer the possibility of simple statistical frequency analyses, generally based on bibliographic patent data. Theses tools can be especially used for identifying trends. One example of such a statistical analysis can be seen in Fig. 1. For the generation of the shown diagrams the tool PATSTAT was used [16].

Beyond such statistical analysis features, some of the patent data analysis tools also provide the possibility to analyze the unstructured technical content part of patents. For this complex content extraction text and data mining methods are needed [24] [18]. By the usage of text and data mining algorithms relevant keywords or phrases which roughly describe a technology can be extracted from patents. These algorithms are based on methods of computational linguistics as well as on Natural Language Processing (NLP) methods in order to enable a high quality of content extraction [14]. This is also referred to as a semantic patent analysis [20]. For the content extraction of patent text algorithms are used, which "understand" the patents and further more or less automatically classify or cluster patents with similar content [8]. Depending on the desired accuracy of the results often vector-based methods are used for classification and clustering, so-called Support Vector Machines [12].

The results of those text mining based patent analyses are generally visualized by different types of so called patent maps, containing the extracted technological information [2]. Fig. 2 shows an example of such a patent map build upon keywords.

Besides text mining results also the results of statistical analyses can be represented by simple maps (e.g. citation or priority maps) [22].

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2011 Proceedings of PICMET '11: Technology Management In The Energy-Smart World (PICMET)

Fig. 1: Example of a statistical analysis of the hybrid cars sector (B60K), created with PATSTAT [14]

Fig. 2: Example of a patent map generated by Themescape (Source: © 2008, Thomson Reuters)

The following table 1 gives an overview of current

software solutions providing single patent search or statistical analysis functions as well as more complex patent mapping functions. The software solutions listed in table 1 that provide the possibility of creating patent maps by using text mining methods for content extraction have in common, that these maps contain only single keywords or key phrases extracted from patents (see example in Fig. 2). Thereto only rough technical information can be extracted from patents with these tools. Another fact is that the extracted keywords and

key phrases not necessarily represent the main quintessence of the document [15]. This can lead to incomplete or wrong interpretation of a patent map and therefore to wrong conclusions for research and development. Especially if patent information is needed as an input for the development of new ideas in research and development, often more detailed technical information is wanted and afforded. Hence there is a need for a method as well as a software solution that extracts more detailed information from patents. In order to address this need we developed the software based White Spot Analysis.

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TABLE 1: PROVIDER OF SOFTWARE SOLUTIONS FOR PATENT DATA ANALYSIS AND WHAT THEY PERFORM (IN ALPHABETICAL ORDER)

Software Provider Patent Search Statistical Analysis Maps

DELPHION Thomson Reuters X XInnography IP Strategy Innography X X XIntellixir Intellixir X (X)

Invention Navigator SIP GmbH X X

IPInquest IP Century AG X X X

IPVision IPVision, Inc. X X X

KMX Patent Analytics Suite Treparel Information Solutions B.V. X X

Matheo Analyzer Matheo-Software(X)

(Matheo Patent)X X

M-CAM Doors M-CAM, Inc. XPatbase Minesoft Ltd X X

Patent Matrix®, Spore®-Search Neopatents X X X

Patentexplorer, Patentstrategist InTraCoM GmbH X X XPatentLabII (only with DELPHION) Wisdomain, Inc. X

Patstat European Patent Office (X) X X

Portfolio DSS Enterprise solution PatentCafeX

(ProSearch Module)X X

ThemeScape (former Aureka) Thomson Reuters X X

VantagePoint Search Technology, Inc. X XWIPS Global WIPS CO. Ltd. X X X

Other Data/Text Mining Software (without focus on patents)

ConWeaver ConWeaver GmbH X X

Knowledgist /Goldfire Invent ionMachine X

Luxid® TEMIS Group X XSpotfire Tibco X X

SWAPit DocMINER Fraunhofer FIT X X

III. INTRODUCTION OF THE WHITE SPOT ANALYSIS

Compared for example to TRIZ the aim of the White Spot

Analysis is not to identify essential problem-solving principles and using them as a basis for the creativity process. The problems and solutions analyzed within the White Spot Analysis process are not mandatory essential but refer to the main claim of the patent. If it is necessary also problems and solutions referring to further claims can be considered during the analysis. In addition only patents of selected technology fields are used for the White Spot Analysis, so only problems and solutions of those special fields are used as a basis for the creativity process.

The basic idea of the White Spot Analysis is known at least since the publication of the “Guide Book for Practical Use of: Patent Map for Each Technology Field” of the Japan Patent Office [11]. At that time efficient text mining software wasn’t available and therefore all patent maps were manually created. Another example of a White Spot Analysis can be found in a technology report regarding nanotechnology of the German Verein Deutscher Ingenieure (VDI) [17]. Both examples have in common that the introduced patent maps deliver a short overview of technical problems and solutions

described in the patents of a dedicated technology field (via keywords and phrases). But they only provide a rough overview and no detailed technical information.

Last but not least the patent application “Methodologies and analytics tools for identifying white space opportunities in a given industry” must be mentioned (US 2008/0195568 A1). This patent application focuses on the identification of white spaces where “little or nor IP may exist”, too. But the analysis is primarily based on the extraction of keywords and focuses on the creation of a classification taxonomy for patents.

As mentioned above, the White Spot Analysis we developed contains as a core element a detailed analysis of problems and solutions described in patents [23]. But to assist the content extraction process special text-mining software was selected and adapted. One aim of our White Spot Analysis is to provide more technical information than a few keywords or non comprehensive phrases as well as a high quality of the extracted content. Another aim is to integrate competitive intelligence aspects (read more about patent analysis for competitive intelligence e.g. [3]). Therefore we go beyond patent facts and combine patent information with market-based as well as company related information in order

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to enhance strategic decisions during the technology management process. For example answers the White Spot Analysis following strategic questions: Is there an attractive gap for own developments in the

patent landscape of a technology field? Does a technical solution, which can be applied to my

problem, already exist in relevant patents? What solutions can be transferred to other applications

and which markets can also be addressed with my technology?

A. Short overview of the White Spot Analysis:

The complete process of our White Spot Analysis is shown in the following Fig. 3.

Before starting the analysis a dedicated technical problem or question should be identified. The technology field for the following analysis should be determined as narrow as possible. The first step of the White Spot Analysis is the patent search which provides the patent documents for the following analysis steps. The patent search is an iterative process and can be repeated several times.

The second step is the detailed content extraction of the selected patents, especially the extraction of described problems and solutions. This extraction is assisted by the special adjusted text-mining software.

In the subsequent step a sort of patent map is generated based on the extracted problems and solutions, the so called problem solution matrix. The problem solution matrix reveals blank cells representing new combinations of problems and solutions, which are not described through a patent yet.

In the following fourth step those blank cells in the matrix, the so called White Spots, are assessed regarding three aspects: first of all, the technical feasibility is checked for each blank cell in the matrix. Only White Spots with a significant technical potential are of interest for further

development steps. After this step, the market-based as well as company related potential is determined for each White Spot with a high technical feasibility. In the last process step the results of the market-based and company related assessment are presented in a portfolio, highlighting the White Spots with the highest overall potential for research and development.

The following chapters describe in detail the White Spot Analysis within the technology field “battery management system for electric vehicles” (except of the patent search step). B. Extraction of problems and solutions for the identification of White Spots

The extraction of problems and solutions from any amount of patent text is assisted by Luxid®. Luxid® as a classical text mining tool is able to analyse and extract information of structured as well as unstructured data of various sources. But originally Luxid® was not able to extract problems or solutions of patents, for this purpose we wrote a special Skill CartridgeTM for patents (in cooperation with TEMIS Deutschland GmbH). A Skill CartridgeTM enables the user to individually adapt the content extraction process that means with this cartridge the user defines which content (e.g. keywords of a technology field, names or dates) should be extracted.

The information extraction approach of our Patent Skill CartridgeTM is not based on the known extraction of special subject-action-object-structures (SAO structures), as e.g. used in TRIZ [8] [13]. Instead of that, the Patent Skill CartridgeTM extracts problems and solutions by the use of special problem or solution indicating phrases und therefore uses the advantage that most of the patents are structured the same way. They commonly provide an abstract, a description part as well as a claim section in the same order. But not only

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Fig.4: Example of the extraction of problems and solutions described in a patent via Luxid® (only in combination with the Patent Skill CartridgeTM)

does the rough textual structure of patents look similar irrespective of the analysed technology field. We identified, that also special sentence structures recur in several patents, e.g. after “In order to prevent…” or “A drawback associated with… is that …” often follows a description of a technical problem. Analogue to the identification of problems we identified special phrases that indicate invented solutions: e.g. after “it is therefore an object of the present invention to provide…” or “to overcome the above shortcomings the present invention provides…” always follows a short description of solution details. An example of the extraction results of the patent skill cartridge is shown in the following Fig. 4.

The main advantage of this approach is, that patents of all technology fields can be analysed by using only one Patent Skill CartridgeTM. For example there is no need of an integration of a technology specific concepts and relations better known as ontologies [4].

For the development of the Patent Skill CartridgeTM key phrases of approximately 100 patents regarding electric vehicles and battery management systems therefore have

been analyzed. At least 100 phrases indicating problems as well as solutions have been extracted and implemented in the Patent Skill CartridgeTM.

Another advantage is that the Patent Skill CartridgeTM can be extended continuously by the user. It is a fact, that by analyzing 100 patens only a low percentage of all problem or solution indicating phrases have been identified yet. In addition to the adaption of the Patent Skill CartridgeTM the Luxid® user is also able to add or delete manually problems or solutions he is not interested in (via the “Dynamic Mapping” functionality). Therefore the user can optimize the extraction results in iterative steps. C. Identification of White Spots

On the basis of the patent content extraction results of Luxid® the problem solution matrix is generated. This matrix is a cross table build of the vertically listed description of problems and horizontally listed description of solutions. The problem solution matrix can be generated by Luxid® and exported to Microsoft Excel for further analysis steps. All listed problems and solutions the matrix contains are

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generally sorted in alphabetical order. An example of a problem solution matrix of 30 analysed patents regarding electric vehicles and battery management systems is shown in Fig. 5. For each patent at least one problem as well as one solution was extracted, generating a matrix of more than 30 rows and columns. As in Fig. 5 can be seen a lot of free cells within the matrix can be identified, each patented problem solution combination is represented with a numbered cell. Those cells are problem and solution combinations not described through a patent yet, the White Spots. But not every White Spot must provide a technically feasible or challenging new idea.

The following Fig. 6 shows three examples of not feasible or useful problem solution combinations (orange cells). White Spot 1 for example intends the possibility that

“monitoring the battery status of an electric vehicle even after the key switch has been turned off” somehow solves the problem of “energy efficient route planning”. But when a vehicle is parked energy efficient route planning must not be of mandatory interest for a user and therefore solutions for parked vehicles must not solve route planning questions. White Spot 2 intends the possibility that a battery management system, designed amongst others for monitoring the state of charge of a plurality of battery cells, solve the problem of “excessive internal generator temperature”. This is a problem solution combination that doesn’t provide any suitable problem solving idea. White Spot 3 is also technically not feasible because a solution for managing the state of charge of batteries doesn’t influence the problem of “fossil fuel consumption or emission efficiency” in any way.

Fig. 5: Excerpt of a problem solution matrix generated by the Patent Skill CartridgeTM of Luxid® regarding battery management systems for electric vehicles

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Fig. 6: Example of White Spots that are not technically feasible or useful

But the decision whether a White Spot is technically

useful and feasible or not often isn’t that that easy. In this case special creativity techniques like brainstorming during workshops with experts are afforded to identify the technical potential of a White Spot.

After completing the feasibility of each empty cell in the problem solution matrix only a few White Spots are left for the following assessment phase.

Within our example case of “battery management systems for electric vehicles” the following White Spots were identified as technically interesting: the described problem “help the user where to charge the vehicle” may be solved by the integration of charging infrastructure information into battery management systems, e.g. in combination with an on-board navigation system. Another problem “malfunction of the battery pack and increase safety” isn’t solved sufficiently yet. Especially the safety aspect (for the vehicle user) is neglected in the analysed patents and provides a high development potential. For the development of appropriate solutions further research must be done. D. Assessment of technically feasible White Spots

The aim of the assessment phase is to evaluate which technically feasible White Spot provides the highest impact regarding market-based and company related aspects. This

assessment is most efficiently done by a simple rating system based on a special set of weighted criteria. For the two dimensions (market-based or company related) a set of five to ten assessment criteria can be individually selected. For the assessment of the criteria we use a simple rating scale, ranging from 1 (meaning very bad) to 5 (meaning very good).

For the market-based assessment of the White Spots a variety of criteria can be selected, depending on the existing and accessible market information. In some cases only a broad research in several databases delivers the information needed for an accurate assessment of the White Spots. If the research includes internet and internal database we also use Luxid® to assist the extraction of relevant content. Therefore we develop specific Skill CartridgesTM to extract the technology specific content.

For the company related assessment of the White Spots we use company specific data based on already measured key performance indicators. The selection of the company related assessment criteria is therefore very individual and may vary between different technologies. The company related assessment criteria are aligned to key performance indicators because this reduces the information gathering process and therefore the assessment effort.

The following Fig. 7 shows an example of market-based as well as company related criteria.

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Fig. 7: Example set of assessment criteria (normalized values)

E. Final rating of the White Spots

When the assessment of the selected White Spots is completed the results can be displayed in a portfolio representing the market-based and company related potential for each White Spot. Therefore we calculate a total value for the market-based as well as company related dimension on the basis of the weighted criteria assessment results. The following Fig. 8 shows an example of the final ranking of White Spots.

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Fig. 8: Portfolio representing the results of the assessment of the White Spots

All White Spots with a high market-based as well as

company related assessment score are of particular interest for the further development process. These White Spots are characterized by a significant technological gap, they can be developed efficiently with respect to the companies resources and they have a high market potential or attractiveness. Especially the blue White Spot representing in our example the “integration of charging infrastructure information into battery management systems, e.g. in combination with an on-board navigation system” has been rated with the highest potential.

IV. WORKING WITH THE WHITE SPOT ANALYSIS

The method of the White Spot Analysis is primarily developed for experts working in research and development. The expert is able to analyze patents of a previous selected technology field with a focus on finding new solutions for his own technical problem. Or he can analyze the problem-solution matrix built upon the selected patents with a focus on finding other problems fitting to his existing solutions. So the White Spot Analysis may answer his questions “Does a solution already exist for my technical problem?” or “I have a good working solution. Are there any problems I can also solve with my solution?” Further on the White Spot Analysis can be used to get an overview of the technology skills of competitors, if the problems and solutions are sorted by the inventors of the patents they were derived from.

But the White Spot Analysis not only gives answers to technical questions, the method is also valuable as a basis for investment decisions in research and development. Because of the assessment process as described in the chapters D. to E. only new ideas with a high market-based and company related value will be developed further to market-ready products. So the risk of investing in ideas that will not be successful in the market because of reasons like “the technology of the competitor already substitutes my solution” or “lack of knowledge about the missing of marketing cannels leaded to losses” is reduced.

The White Spot Analysis may also be used as a basis for decisions within strategic technology management processes. If the White Spot Analysis is repeated continuously (e.g. once a year), the development of technologies within the selected technology field can be monitored and trends can be identified.

REFERENCES [1] Altshuller, G., Altov, H.; And suddenly the inventor appeared: TRIZ,

the Theory of Inventive Problem Solving. Worcester, MA: Technical Innovation Center, Inc., 1994-2004

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[2] Bettray, S.; “Patent Maps - Landkarten der Innovation,“ Wissensmanagement, vol. 10 (5), pp. 50-51, 2008.

[3] Breitzman, A. F. and Mogee, M. E.; “The many applications of patent analysis,” Journal of Information Science, vol. 28 (3), pp. 187-205, 2002.

[4] Chokri, B. N.; Ontology-based Semantic Query Processing in Database Systems. Berlin: Humboldt-University, 2006.

[5] Cooper, R. G. and Edgett, S. J.; Generating Breakthrough New Product Ideas: Feeding the Innovation Funnel. Canda: Booksurge Llc, 2009.

[6] Daim, T.U. and Rueda, G. and Martin, H. and Gerdsri, P.; “Forecasting emerging technologies: Use of bibliometrics and patent analysis,” Technological Forecasting & Social Change, vol. 73, pp. 981-1012, 2006.

[7] Dou, H. and Leveillé, V. and Manullang, S. and Dour, J. M. Jr.; “Patent analysis for competitive technical intelligence and innovative Thinking,” Data Science Journal, vol. 4, pp. 209-237, 2005.

[8] Dreßler, A.; Patente in technologieorientierten Mergers & Acquisitions - Nutzen, Prozessmodell, Entwicklung und Interpretation semantischer Patentlandkarten. Wiesbaden: Deutscher Universitäts-Verlag, 2006.

[9] Ernst, H.; “Patent information for strategic technology management,” World Patent Information, vol. 25, pp. 233-242, 2003.

[10] Fall, C. J. and Benzineb, K.; “Literature Survey: Issues to be considered in the automatic classification of patents,” World Intellectual Property Organization, working paper, 2002.

[11] Japan Patent Office; “Guide Book for Practical Use of - Patent Map for Each Technology Field,” Retrieved 10/01/11 World Wide Web, http://202.106.92.141/shangchuan/zmyj0009.pdf

[12] Joachims, T.; “Text Categorization with Support Vector Machines: Learning with Many Relevant Features,” Proceedings of ECML-98, 10th European Conference on Machine Learning, working paper, 1998.

[13] Kalogerakis, K.; Innovative Analogien in der Praxis der Produktentwicklung. Hamburg-Wiesbaden: Gabler Verlag, 2010

[14] Kao, A., and Poteet, S. R.; Natural language processing and text mining. London: Springer-Verlag London Ltd., 2007.

[15] Li, Y.-R. and Wang, L.-H. and Hong, C.-F.; “Extracting the significant-rare key-words for patent analysis,” Expert Systems with Applications, vol. 36, pp. 5200-5204, 2009.

[16] Lingua, D. and Schaaf., J.; “Patent mapping and patent statistics,” Retrieved 23/2/11 World Wide Web, http://documents.epo.org/projects/babylon/eponet.nsf/0/9416F293EBFFDD66C125750E0047C359/$File/Patent_mapping_example_B60K_Hybrid_car_en.pdf

[17] Luther, W. and Malanowski, N.; “Nanotechnologie als wirtschaftlicher Wachstumsmarkt - Innovations- und Technikanalyse“, Zukünftige Technologien Consulting der VDI Techno-logiezentrum GmbH, working paper, 2004

[18] March, R. W.; “Text mining patent literature: a case scenario of a methodology for analyzing unstructured data,” Searcher Information Today Inc., 2008.

[19] Mittelstädt, A.; Strategisches IP-Management – mehr als nur Patente: Geistiges Eigentum schützen und als Wettbewerbsvorsprung nutzen. Wiesbaden: Gabler, 2009.

[20] Möhrle, M. G. and Walter, L. and Geritz, A.; “Semantische Patentanalyse mit dem Knowledgist und PIA: Grundlagen - Beispiele - Kritik,” PATINFO 2003, TU Illmenau, conference paper, 2003.

[21] Porter, A. L., Cunningham, S. W.; Tech mining: exploiting new technologies for competitive advantage. Hoboken, New Jersey: John Wiley & Sons, Inc., 2005

[22] Schaaf, J.; “Patent statistics and patent mapping,” Retrieved 23/2/11 World Wide Web, http://documents.epo.org/projects/babylon/eponet.nsf/0/16D96F274CD7E298C12575070055E00E/$File/schaaf_en.pdf

[23] Spath, D. Siwczyk, Y; IT-gestützte White-Spot-Analyse – Potenziale von Patentinformationen am Beispiel Elektromobilität erkennen. Stuttgart: Fraunhofer Verlag, 2010.

[24] Zeller, A.; Technologiefrühaufklärung mit Data Mining - Informations-prozessorientierter Ansatz zur Identifikation schwacher Signale. Stuttgart: Gabler, 2003.

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