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Fraunhofer IAO conducted a study among 1,000 German innovation professionals regarding their webbased information acquisition needs. The study showed the need for search tools and methods optimised for the target group of innovation professionals. In this paper we deduce accordant concepts from the study’s results. We suggest an “Innovation Mining Process” as a structured approach to web-based information acquisition for early innovation phases. Our software prototype the Innovation Mining Cockpit (IMC) picks up essential concepts of this process and implements them as an easy-to-use web portal. The IMC is intended as a central point of contact for innovation-related search activities. 1 WEB SEARCHING IN INNOVATION MANAGEMENT Innovative ideas can be the result of both formal and unstructured search processes and can have many different origins. The Internet provides access to external innovation sources in multiple and comfortable ways. However, the analysis process remains a complicated one: it is often unclear where the relevant information is located. Furthermore, classical search engines do not offer a sufficient precision to filter the results and separate the relevant ones from the large amount of irrelevant ones. In a 2009 survey among innovation professionals, Fraunhofer IAO analyzed the Web searching requirements of innovation professionals in Germany (Finzen, Krepp and Heubach, 2009). Figure 1 summarizes the findings regarding the importance of different Web-based information sources regarding different steps of the early innovation phases: “innovation push”, “idea collection”, “idea creation”, and “idea evaluation”. While online journals and research and technology portals are used for finding innovation impulses and collecting ideas, encyclopedias and especially patent databases are most useful for idea evaluation. Internet-based information sources are considered most useful for collecting ideas, but less useful for the actual creation of ideas. Figure 1: Importance of Internet-based information sources for different (early) innovation phases (n=142). We questioned the respondents about the most annoying problems they encounter with search engines. More interesting than the obvious aspects quality and time-efficiency however seem the remaining ones: almost half of the respondents claimed that they miss a ranking according to up-todateness and almost 40 percent are not satisfied with the available filter mechanisms. 241 Finzen J. and Kintz M.. INNOVATION MINING Supporting Web Mining in Early Innovation Phases. DOI: 10.5220/0003276202410247 In Proceedings of the 7th International Conference on Web Information Systems and Technologies (WEBIST-2011), pages 241-247 ISBN: 978-989-8425-51-5 Copyright c 2011 SCITEPRESS (Science and Technology Publications, Lda.) Figure 2: Importance of search engine features (n=142). The results clearly show that there is a demand for a new generation of search tools tailored to the needs of innovation professionals. 2 INNOVATION MINING CONCEPTS From both the results of our survey described above as well as from discussions with industrial customers we deduce several requirements that innovation mining tools must take into consideration. These requirements are discussed in the following sections. 2.1 Incorporate User Knowledge Innovation professionals are considered to have a deep domain competence and bring along a broad knowledge of where and how to find information meeting their requirements and needs (“source competence”). It seems promising to make use of both the domain and the source competence as much as possible within a professional information acquisition tool, e.g. by  allowing the users to integrate their favourite information source with little effort, and  integrating domain knowledge into the search process. This can be done, for example, by hierarchically or ontologically structuring domain knowledge and providing both search queries and result sets for respective nodes. 2.2 Deal with Multitude of Relevant Information Sources As shown in Figure 1 there are many kinds of information sources that are relevant to innovation management. Depending on the actual phase of the innovation process, some of these information sources are more important than others. According to our survey, the majority of respondents liked the idea of having multiple information sources integrated and accessible via a unified point of access. We divide the information sources available on the web into three different levels: 1. The Document Level: On the most basic level, single documents are accessed directly. E.g., the Fraunhofer website can be accessed by the user assuming to find the site at www.fraunhofer.de. 2. The Database or Search Engine Level: For most types of documents, specialised search tools already exist that offer advanced functionality to retrieve and present information. E.g., there are numerous search engines for scientific content, and web-based patent databases make it easy to search for patents on a given subject. To integrate such sources, a tool has to “speak” and “understand” the same “language”, i.e., know how to formulate and send a search query to the search engine and how to grab and interpret the results. This is commonly known as “meta search”. 3. The Meta Search Level: For some kind of information, meta search engines already exist. Accessing meta search engines requires basically the same requirements and process steps as for “normal” search engines, but is has to be kept in mind that one relies on the “language translation step” being executed by the meta search engine and thus not being under one’s own control. One challenge of providing an integrated information acquisition tool for innovation mining thus lies in the handling of “different languages” of different information sources. 2.3 Use Document-specific Metadata There are many different document types relevant for innovation mining process, like e.g. patent data, scientific papers, press releases, or blog entries. Each of these document types has specific attributes and metadata that can be exploited within innovation mining: Press releases always have a publishing date and address information which make it easy to order and visualize them accordingly (Finzen, Kintz, Koch and Kett, 2009). Scientific literature can be a basis for expert identifiaction using co-authorship analyses. Patent data can be exploited for e.g. white spot analysis (Siwcyk, 2009). WEBIST 2011 7th International Conference on Web Information Systems and Technologies

INNOVATION MINING - Supporting Web Mining in Early Innovation Phases