Search (3 results, page 1 of 1)

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Abstract

Accidental Information Discovery: Cultivating Serendipity in the Digital Age provides readers with an interesting discussion on the ways serendipity-defined as the accidental discovery of valued information-plays an important role in creative problem-solving. This insightful resource brings together discussions on serendipity and information discovery, research in computer and information science, and interesting thoughts on the creative process. Five thorough chapters explore the significance of serendipity in creativity and innovation, the characteristics of serendipity-friendly tools and minds, and how future discovery environments may encourage serendipity. - Examines serendipity in a multidisciplinary context - Bridges theory and practice - Explores digital information landscapes of the future with essays from current researchers - Brings the concept of accidental discovery and its value front and center

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Abstract

The 4th edition of this popular and well-cited text is now co-authored, and includes significant changes from earlier texts. Presenting a comprehensive review of over a century of research on information behavior (IB), this book is intended for students in information studies and disciplines interested in research on information activities. The initial two chapters introduce IB as a multi-disciplinary topic, the 3rd provides a brief history of research on information seeking. Chapter four discusses what is meant by the terms "information" and "knowledge. "Chapter five discusses "information needs," and how they are addressed. The 6th chapter identifies many related concepts. Twelve models of information behavior (expanded from earlier editions) are illustrated in chapter seven. Chapter eight reviews various paradigms and theories informing IB research. Chapter nine examines research methods invoked in IB studies and a discussion of qualitative and mixed approaches. The 10th chapter gives examples of IB studies by context. The final chapter looks at strengths and weaknesses, recent trends, and future development.

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Abstract

Recent technological progress in computer science, Web technologies, and constantly evolving information available on the Internet has drastically changed the landscape of search and access to information. Web search has significantly evolved in recent years. In the beginning, web search engines such as Google and Yahoo! were only providing search service over text documents. Aggregated search was one of the first steps to go beyond text search, and was the beginning of a new era for information seeking and retrieval. These days, new web search engines support aggregated search over a number of vertices, and blend different types of documents (e.g., images, videos) in their search results. New search engines employ advanced techniques involving machine learning, computational linguistics and psychology, user interaction and modeling, information visualization, Web engineering, artificial intelligence, distributed systems, social networks, statistical analysis, semantic analysis, and technologies over query sessions. Documents no longer exist on their own; they are connected to other documents, they are associated with users and their position in a social network, and they can be mapped onto a variety of ontologies. Similarly, retrieval tasks have become more interactive and are solidly embedded in a user's geospatial, social, and historical context. It is conjectured that new breakthroughs in information retrieval will not come from smarter algorithms that better exploit existing information sources, but from new retrieval algorithms that can intelligently use and combine new sources of contextual metadata.

Content

Vert, S.: Extensions of Web browsers useful to knowledge workers. Chen, L.-C.: Next generation search engine for the result clustering technology. Biskri, I., L. Rompré: Using association rules for query reformulation. Habernal, I., M. Konopík u. O. Rohlík: Question answering. Grau, B.: Finding answers to questions, in text collections or Web, in open domain or specialty domains. Berri, J., R. Benlamri: Context-aware mobile search engine. Bouidghaghen, O., L. Tamine: Spatio-temporal based personalization for mobile search. Chaudiron, S., M. Ihadjadene: Studying Web search engines from a user perspective: key concepts and main approaches. Karaman, F.: Artificial intelligence enabled search engines (AIESE) and the implications. Lewandowski, D.: A framework for evaluating the retrieval effectiveness of search engines.