A Survey of Text Mining Techniques and Applications <s> 1) Competitive Intelligence: <s> This paper describes how an integrated web-based application, code-named FOCI (Flexible Organizer for Competitive Intelligence), can help the knowledge worker in the gathering, organizing, tracking, and dissemination of competitive intelligence or knowledge bases on the web. It shows how text mining techniques including a novel user-configurable clustering, trend analysis and visualization techniques can be used synergistically to address the problem of managing information gathered from the web. FOCI allows a user to define and personalize the organization of the information clusters according to their needs and preferences into portfolios. Predefined sections for organizing information in specific domains is also supported. The personalized portfolios created can be saved and subsequently tracked and shared with other users. In addition, FOCI is designed to handle multilingual documents. <s> BIB001 </s> A Survey of Text Mining Techniques and Applications <s> 1) Competitive Intelligence: <s> In order to delineate the state of the art of the main TM applications a two-step strategy has been pursued: first of all, some of the main European and Italian companies offering TM solutions were contacted, in order to collect information on the characteristics of the applications; secondly, a detailed search on the web was made to collect further information about users or developers and applications. On the basis of the material collected, a synthetic grid was built to collocate, from more than 300 cases analysed, the 100 ones that we considered most relevant for the typology of function and sector of activity. The joint analysis of the different case studies has given an adequate picture of TM applications according to the possible types of results that can be obtained, the main specifications of the sectors of applications and the type of functions. Finally it is possible to classify the applications matching the level of customisation (followed in the tools development) and the level of integration (between users and developers). This matching produces four different situations: standardisation, outsourcing, internalisation, synergism. <s> BIB002
The need to organize and modify their strategies according to demands and to the opportunities that the market present requires that companies collect information about themselves, the market and their competitors, and to manage enormous amount of data, and analyzing them to make plans. The aim of Competitive Intelligence BIB002 is to select only relevant information by automatic reading of this data. Once the material has been collected, it is classified into categories to develop a database, and analyzing the database to get answers to specific and crucial information for company strategies. The typical queries concern the products, the sectors of investment of the competitors, the partnerships existing in markets, the relevant financial indicators, and the names of the employees of a company with a certain profile of competences. Before the introduction of TM, there was a division that was entirely dedicated to the continuous monitoring of information (financial, geopolitical, technical and economic) and answering the queries coming from other sectors of the company. In these cases the return on investment by the use of TM technologies was self evident when compared to results previously achieved by manual operators. In some cases, if a scheme of categories is not defined a priori, cauterization procedures are used to classify the set of documents (considered) relevant with regard to a certain topic, in clusters of documents with similar contents. The analysis of the key concepts present in the single clusters gives an overall vision of the subjects dealt with in the single texts. More company and news information are increasingly available on the web. As such, it has become a gold mine of online information that is crucial for competitive intelligence (CI). To harness this information, various search engines and text mining techniques have been developed to gather and organize it. However, the user has no control on how the information is organized through these tools and the information clusters generated may not match their needs. The process of manually compiling documents according to a user's needs and preferences and into actionable reports is very labour intensive, and is greatly amplified when it needs to be updated frequently. Updates to what has been collected often require a repeated search, filtering of previously retrieved documents and re-organizing. FOCI BIB001 (Flexible Organizer for Competitive Intelligence), can help the knowledge worker in the gathering, organizing, tracking, and dissemination of competitive intelligence or knowledge bases on the web. FOCI allows a user to define and personalize the organization of the information clusters according to their needs and preferences into portfolios. Figure16 shows the architecture of FOCI. It comprises an Information Gathering module for retrieving relevant information from the web sources; a Content Management module for organizing information into portfolios and personalizing the portfolios; a Content Mining module for discovering new information and a Content Publishing module for publishing and sharing of information and a user interface front end for graphical visualization and users interactions. The portfolios created are stored into CI knowledge bases which can be shared by the users within an organization. 