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Belkin, N.J.: ¬An overview of results from Rutgers' investigations of interactive information retrieval (1998) 0.03
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Abstract

Over the last 4 years, the Information Interaction Laboratory at Rutgers' School of communication, Information and Library Studies has performed a series of investigations concerned with various aspects of people's interactions with advanced information retrieval (IR) systems. We have benn especially concerned with understanding not just what people do, and why, and with what effect, but also with what they would like to do, and how they attempt to accomplish it, and with what difficulties. These investigations have led to some quite interesting conclusions about the nature and structure of people's interactions with information, about support for cooperative human-computer interaction in query reformulation, and about the value of visualization of search results for supporting various forms of interaction with information. In this discussion, I give an overview of the research program and its projects, present representative results from the projects, and discuss some implications of these results for support of subject searching in information retrieval systems

Date

22. 9.1997 19:16:05

Belkin, N.J.; Croft, W.B.: Retrieval techniques (1987) 0.03

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Source: Annual review of information science and technology. 22(1987), S.109-145

Belkin, N.J.: ¬The problem of 'matching' in information retrieval (1980) 0.02

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Source: Theory and application of information research. Proc. of the 2nd Int. Research Forum on Information Science, 3.-6.8.1977, Copenhagen. Ed.: O. Harbo u. L. Kajberg

Belkin, N.J.; Vickery, A.: Interaction in information systems : a review of research from document retrieval to knowledge-based systems (1985) 0.02

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Belkin, N.J.; Chang, S.J.; Downs, T.; Saracevic, T.; Zhao, S.: Taking account of user tasks, goals and behavior for the design of online public access catalogs (1990) 0.01

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Source: ASIS'90: Information in the year 2000: from research to application. Proc. 33rd Annual Meeting of the American Society for Information Science

Yuan, X. (J.); Belkin, N.J.: Applying an information-seeking dialogue model in an interactive information retrieval system (2014) 0.01

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Date: 6. 4.2015 19:22:59

Belkin, N.J.: ¬The use of multiple information problem representation for information retrieval (1994) 0.01
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Abstract

Discusses the general issues of the effect and use of multiple representations of the same information problem, or topics, on information retrieval system performance. It has been known for some time that different representations of the same information problem retrieve different sets (or lists) of documents, both relevant and non-relevant. More recently, there have been a number of studies investigating the effects of combining, in various ways, such different representations, in order to try to get a single response from the information retrieval system which is better than that for any of the single representations. Discusses the rationale, both empirical and theoretical, for such an approach, and surveys the results of recent research projects in this area. All of them demonstrate the same phenomenon; the more representations one can combine, the better the retrieval performance. Discusses the implications of these results for information retrieval system design and information retrieval
Murdock, V.; Kelly, D.; Croft, W.B.; Belkin, N.J.; Yuan, X.: Identifying and improving retrieval for procedural questions (2007) 0.01
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Abstract

People use questions to elicit information from other people in their everyday lives and yet the most common method of obtaining information from a search engine is by posing keywords. There has been research that suggests users are better at expressing their information needs in natural language, however the vast majority of work to improve document retrieval has focused on queries posed as sets of keywords or Boolean queries. This paper focuses on improving document retrieval for the subset of natural language questions asking about how something is done. We classify questions as asking either for a description of a process or asking for a statement of fact, with better than 90% accuracy. Further we identify non-content features of documents relevant to questions asking about a process. Finally we demonstrate that we can use these features to significantly improve the precision of document retrieval results for questions asking about a process. Our approach, based on exploiting the structure of documents, shows a significant improvement in precision at rank one for questions asking about how something is done.
Liu, J.; Liu, C.; Belkin, N.J.: Predicting information searchers' topic knowledge at different search stages (2016) 0.01
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Abstract

As a significant contextual factor in information search, topic knowledge has been gaining increased research attention. We report on a study of the relationship between information searchers' topic knowledge and their search behaviors, and on an attempt to predict searchers' topic knowledge from their behaviors during the search. Data were collected in a controlled laboratory experiment with 32 undergraduate journalism student participants, each searching on 4 tasks of different types. In general, behavioral variables were not found to have significant differences between users with high and low levels of topic knowledge, except the mean first dwell time on search result pages. Several models were built to predict topic knowledge using behavioral variables calculated at 3 different stages of search episodes: the first-query-round, the middle point of the search, and the end point. It was found that a model using some search behaviors observed in the first query round led to satisfactory prediction results. The results suggest that early-session search behaviors can be used to predict users' topic knowledge levels, allowing personalization of search for users with different levels of topic knowledge, especially in order to assist users with low topic knowledge.

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