Living Knowledge

Diversity, especially manifested in language and knowledge, is a function of local goals, needs, competences, beliefs, culture, opinions and personal experience. The Living Knowledge project considers diversity as an asset rather than a problem. With the project, foundational ideas emerged from the synergic contribution of different disciplines, methodologies (with which many partners were previously unfamiliar) and technologies flowed in concrete diversity-aware applications such as the Future Predictor and the Media Content Analyser providing users with better structured information while coping with Web scale complexities. The key notions of diversity, fact, opinion and bias have been defined in relation to three methodologies: Media Content Analysis (MCA) which operates from a social sciences perspective; Multimodal Genre Analysis (MGA) which operates from a semiotic perspective and Facet Analysis (FA) which operates from a knowledge representation and organization perspective. A conceptual architecture that pulls all of them together has become the core of the tools for automatic extraction and the way they interact. In particular, the conceptual architecture has been implemented with the Media Content Analyser application. The scientific and technological results obtained are described in the following

Longitudinal analysis of search engine query logs - temporal coverage

Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2012.Thesis (Master's) -- Bilkent University, 2012.Includes bibliographical references leaves 53-60.The internet is growing day-by-day and the usage of web search engines is continuously increasing. Main page of browsers started by internet users is typically the home page of a search engine. To navigate a certain web site, most of the people prefer to type web sites’ name to search engine interface instead of using internet browsers’ address bar. Considering this important role of search engines as the main entry point to the web, we need to understand Web searching trends that are emerging over time. We believe that temporal analysis of returned query results by search engines reveals important insights for the current situation and future directions of web searching. In this thesis, we provide a large-scale analysis of the evolution of query results obtained from a real search engine at two distant points in time, namely, in 2007 and 2010, for a set of 630000 real queries. Our analyses in this work attempt to find answers to several critical questions regarding the evolution of Web search results. We believe that this work, being a large-scale longitudinal analysis of query results, would shed some light on those questions.Yılmaz, OğuzM.S

From people to entities : typed search in the enterprise and the web

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