Catálogo de publicaciones - libros

Over the last few years, our organization has entered into partnerships with companies in China and Poland. They want insight into our sales and we want the same into the status of our orders with them. That results in functional demands on the information function, which may only be filled in step by step. In a chain, companies that cooperate for a number of years should really exchange data openly and transparently. With our information function and its IT support that is not always as easy as all that.

Developing and supporting human search capabilities is at least equally important as developing the capabilities of search engines. Existing academic research suggests that particularly inexperienced users searching the Web utilize only a modest subset of the capabilities that the tools offer and are weak at understanding their real information needs, articulating them in a way that allows for effective searches, and interpreting search results in the context of those needs. This clearly suggests that training users to become better searchers is a worthwhile effort, and that understanding what makes certain search interventions successful and others not is vitally important for enabling users to make effective use of their time.

Our review of existing search training literature revealed relatively broadly scattered efforts that, to a large extent, were not programmatic or focused on developing well-defined theoretical models. This makes it difficult to integrate findings from different studies into cohesive bodies of work that would support the development and evaluation of new training interventions. In this chapter, we propose three approaches to using existing areas of research as a theoretical foundation for future work. Namely: a) understanding the nature of search processes is very important if we want to understand search training, because different stages of the search process require different training approaches; b) a thorough analysis of search errors forms a solid foundation for training approaches that helps users avoid the common errors; and c) training research from related disciplines, such as information systems, can be used to introduce new theoretical perspectives and suggest models that are also potentially helpful in search training.

Search is pervasive in modern life and performing effective online searches is a fundamentally important literacy skill, not only for 21st century knowledge professionals but for every individual who relies on material available from online sources. Understanding how we, as a research community, can help people become effective searchers is, therefore, of critical importance.

The principle of polyrepresentation is a coherent and comprehensive cognitive framework that can be applied simultaneously to the cognitive space of the user and the information space of IR systems. The principle has the potential to guide the design of interactive IR systems that take full advantage of the available document representations user’s context to improve retrieval performance.

However, before this can be achieved a number of issues need further investigation. Among these are simulation studies that test which methods would be appropriate for matching different representations of the user’s cognitive space with document representations. Such simulations could apply simulated work task situations; or they could explore exhaustively the possibilities of a number of controlled variables and thus simulate all achievable combinations. Investigations involving test persons and experimental laboratory tests (simulations) must take into account the dependency of domains, media and representation styles.

Studies of the principles for how a Request Model Builder should function would be fruitful, and how to match representations to generate strong cognitive overlaps, especially in best match settings. The latter issue is illustrated by the polyrepresentation continuum. It points to the investigation of flexible and powerful hybrid matching of representations as a challenge and opportunity for future research along these lines.

The chapter presented a framework for understanding and studying how behavior can be used as implicit relevance feedback. This included a classification and discussion of behaviors that have been used as implicit relevance feedback, a general discussion and characterization of implicit feedback research, and a presentation of example studies to illustrate how such studies have been conducted and how feedback has typically been measured and used. Finally, this chapter presented a discussion of key issues and problems associated with implicit feedback research and identified challenges for future research. The use of behavior as implicit relevance feedback is an exciting and promising approach to personalizing IR interactions. Although more effort needs to be made to fully understand how behaviors can be used as implicit relevance feedback, current research efforts offer a promising start.

The colossal landscape of scholarly knowledge, growing at exponential rates, now requires representational maps utilizing advanced techniques to provide insight into the structure and dynamics of scholarly domains. Today we need intellectual cartographers to assist students and scholars in navigating, understanding and internalizing the structure and dynamics of scholarly bodies of knowledge. There is compelling evidence of the utility of KDVs stemming from the fields of educational psychology, cognitive science, cartography, and information science. Well designed KDVs have the ability to facilitate understanding, recall, and to convey to the user the schematic, geo-spatial, f temporal, semantic, or social organization of the underlying domain.

Though educational knowledge domain visualizations are still in their infancy, we believe that they have a promising future in assisting with access to and the navigation, understanding, management, and communication of large-scale information spaces. Furthermore, when used as an interface for information retrieval, knowledge domain visualizations have the potential to convey the structural organization of the domain to the user. In turn, this structural knowledge of the domain provides the cognitive scaffolding with which the user may associate additional details about the domain.

The chapter presented a framework for understanding and studying how behavior can be used as implicit relevance feedback. This included a classification and discussion of behaviors that have been used as implicit relevance feedback, a general discussion and characterization of implicit feedback research, and a presentation of example studies to illustrate how such studies have been conducted and how feedback has typically been measured and used. Finally, this chapter presented a discussion of key issues and problems associated with implicit feedback research and identified challenges for future research. The use of behavior as implicit relevance feedback is an exciting and promising approach to personalizing IR interactions. Although more effort needs to be made to fully understand how behaviors can be used as implicit relevance feedback, current research efforts offer a promising start.

At present no overall integrative framework exists for CIR, but an integrated approach—i.e., that distinguishes separate concepts and processes in information seeking and information search then attempts to create an integrated conceptualization of the user who is both searching and seeking information within the larger context of HIB—has the potential to yield a more holistic theoretical and cognitive understanding that will assist IR and Web system designers.

This book provides an overview of new directions in CIR research. The field of CIR is broad, international, interdisciplinary and dynamic with tremendous potential to impact the everyday lives of people in both developed and developing countries as they increasingly need to interact with IR systems. This book is not an exhaustive or historical discussion of all possible areas of important and new directions in CIR research. Information retrieval, in all its technical, cognitive and other respects continues to be an intractable research problem and research area. Our goal in producing this book was to stimulate the thinking of authors and readers alike.

The chapter presented a framework for understanding and studying how behavior can be used as implicit relevance feedback. This included a classification and discussion of behaviors that have been used as implicit relevance feedback, a general discussion and characterization of implicit feedback research, and a presentation of example studies to illustrate how such studies have been conducted and how feedback has typically been measured and used. Finally, this chapter presented a discussion of key issues and problems associated with implicit feedback research and identified challenges for future research. The use of behavior as implicit relevance feedback is an exciting and promising approach to personalizing IR interactions. Although more effort needs to be made to fully understand how behaviors can be used as implicit relevance feedback, current research efforts offer a promising start.

The chapter presented a framework for understanding and studying how behavior can be used as implicit relevance feedback. This included a classification and discussion of behaviors that have been used as implicit relevance feedback, a general discussion and characterization of implicit feedback research, and a presentation of example studies to illustrate how such studies have been conducted and how feedback has typically been measured and used. Finally, this chapter presented a discussion of key issues and problems associated with implicit feedback research and identified challenges for future research. The use of behavior as implicit relevance feedback is an exciting and promising approach to personalizing IR interactions. Although more effort needs to be made to fully understand how behaviors can be used as implicit relevance feedback, current research efforts offer a promising start.

The colossal landscape of scholarly knowledge, growing at exponential rates, now requires representational maps utilizing advanced techniques to provide insight into the structure and dynamics of scholarly domains. Today we need intellectual cartographers to assist students and scholars in navigating, understanding and internalizing the structure and dynamics of scholarly bodies of knowledge. There is compelling evidence of the utility of KDVs stemming from the fields of educational psychology, cognitive science, cartography, and information science. Well designed KDVs have the ability to facilitate understanding, recall, and to convey to the user the schematic, geo-spatial, f temporal, semantic, or social organization of the underlying domain.

Though educational knowledge domain visualizations are still in their infancy, we believe that they have a promising future in assisting with access to and the navigation, understanding, management, and communication of large-scale information spaces. Furthermore, when used as an interface for information retrieval, knowledge domain visualizations have the potential to convey the structural organization of the domain to the user. In turn, this structural knowledge of the domain provides the cognitive scaffolding with which the user may associate additional details about the domain.