Information filtering systems are designed for unstructured or semistructured data, as opposed to database applications, which use very structured data. The systems also deal primarily with textual information, but they may also entail images, voice, video or other data types that are part of multimedia information systems. Information filtering systems also involve a large amount of data and streams of incoming data, whether broadcast from a remote source or sent directly by other sources. Filtering is based on descriptions of individual or group information preferences, or profiles, that typically represent long-term interests. Filtering also implies removal of data from an incoming stream rather than finding data in the stream; users see only the data that is extracted. Models of information retrieval and filtering, and lessons for filtering from retrieval research are presented.

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Information filtering and information retrieval: two sides of the same coin?

10345 Abstract 10346 Abstract 10347 Abstract 10348 :iltered Abstracts Abstract 10349 Abstract 1040210349 Abstract 10402 Highly rated abstracts added to document profile each month T h e score for e ach new T M was t he cos ine b e t w e e n t he T M vec tor a n d the nearest i n t e r e s t vector . T h e new T M s were t h e n r a n k e d based o n the i r m a x i m u m cosine score. T h u s , T M s o c c u r r i n g close to any p o i n t o f i n t e r e s t fo r a p a r t i c u l a r e m p l o y e e would be r a n k e d t he h ighes t . T h e same type o f c o m p a r i s o n was d o n e fo r the d o c u m e n t prof i les . Each docu m e n t in t he d o c u m e n t p rof i l e was r e p r e s e n t e d as a s epa ra t e vec tor a n d c o m p a r e d to all new T M s . T h e new T M s were t h e n r a n k e d based o n the m a x i m u m cosine for e ach T M to any d o c u m e n t in t he d o c u m e n t prof i le . T h e s e c o m p a r i s o n s r e su l t ed in f o u r r a n k o r d e r e d lists o f abstracts , o n e for e ach f i l t e r ing m e t h o d . T h e top abs t rac t s f r o m each m e t h o d were t h e n sen t to each emp loyee , w h o r a t e d t h e m fo r r e l evance to his o r h e r t echn ica l in teres ts . Fo r each m e t h o d , the t op 25% o f t he abs t rac t s r a t e d 4 or h i g h e r were t h e n i n c o r p o r a t e d in to t he e m p l o y e e s ' d o c u m e n t p ro files. 3 I n the f i rs t m o n t h o f s tudy, on ly the w o r d prof i l e was u sed s ince e m p l o y e e s h a d no t p rev ious ly indica ted which abs t rac t s to i nc lude in t h e i r d o c u m e n t prof i le . I n the subseFlOure 11. The f i l t e r i n g p r o c e s s Table 1. The four f i l ter ing methods

Personalized information delivery: an analysis of information filtering methods

This paper offers a new, nonlinear model of information-seeking behavior, which contrasts with earlier stage models of information behavior and represents a potential cornerstone for a shift toward a new perspective for understanding user information behavior. The model is based on the findings of a study on interdisciplinary information-seeking behavior. The study followed a naturalistic inquiry approach using interviews of 45 academics. The interview results were inductively analyzed and an alternative framework for understanding information-seeking behavior was developed. This model illustrates three core processes and three levels of contextual interaction, each composed of several individual activities and attributes. These interact dynamically through time in a nonlinear manner. The behavioral patterns are analogous to an artist's palette, in which activities remain available throughout the course of information-seeking. In viewing the processes in this way, neither start nor finish points are fixed, and each process may be repeated or lead to any other until either the query or context determine that information-seeking can end. The interactivity and shifts described by the model show information-seeking to be nonlinear, dynamic, holistic, and flowing. The paper offers four main implications of the model as it applies to existing theory and models, requirements for future research, and the development of information literacy curricula. Central to these implications is the creation of a new nonlinear perspective from which user information-seeking can be interpreted.

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A nonlinear model of information-seeking behavior

Previous research has shown that there are major differences in the search methods used in different disciplines, and that the use of electronic journals and databases likewise varies according to domain. Previous studies have not, however, explored whether, or how, this variation is possibly related to factors such as domain size, the degree of scatter in a domain or domain‐specific relevance criteria. The aim of this paper is to contribute to the development of a domain analytic approach for explaining the use and non‐use of e‐journals and databases. We identify and define factors to account for disciplinary differences in e‐journal use, outline hypotheses to be tested more rigorously in future research, and test them initially on a limited data set. The empirical data was gathered as a part of a wider qualitative study exploring scholars’ use of networked resources in four different disciplines: nursing science, literature/cultural studies, history and ecological environmental science. The findings suggest that e‐journals and databases are likely to be used most heavily in fields in which directed searching is the dominant search method and topical relevance the primary relevance type, and less in fields in which browsing and chaining are the dominant search methods and paradigmatic relevance the primary relevance type. The findings also support the Bates hypothesis that domain size has an important impact on the search methods used.

Reasons for the use and non‐use of electronic journals and databases: A domain analytic study in four scholarly disciplines

This paper deals with information needs, seeking, searching, and uses within scholarly communities by introducing theory from the field of science and technology studies. In particular it contributes to the domain-analytic approach in information science by showing that Whitley's theory of 'mutual dependence' and 'task uncertainty' can be used as an explanatory framework in understanding similarity and difference in information practices across intellectual fields. Based on qualitative case studies of three specialist scholarly communities across the physical sciences, applied sciences, social sciences and arts and humanities, this paper extends Whitley's theory into the realm of information communication technologies. The paper adopts a holistic approach to information practices by recognising the interrelationship between the traditions of informal and formal scientific communication and how it shapes digital outcomes across intellectual fields. The findings show that communities inhabiting fields with a high degree of 'mutual dependence' coupled with a low degree of 'task uncertainty' are adept at coordinating and controlling channels of communication and will readily co-produce field-based digital information resources, whereas communities that inhabit fields characterised by the opposite cultural configuration, a low degree of 'mutual dependence' coupled with a high degree of 'task uncertainty', are less successful in commanding control over channels of communication and are less concerned with co-producing field-based digital resources and integrating them into their epistemic and social structures. These findings have implications for the culturally sensitive development and provision of academic digital resources such as digital libraries and web-based subject portals.

Scholarly research and information practices: a domain analytic approach

Scope: The purpose of this study was to explore the use and effectiveness of current awareness (CA) methods, especially SDI, among chemists at Canadian universities. Method: We used a questionnaire which was mailed to a sample of 170 (response rate 80%). The variables studied include perceived scatter of information, use of various CA methods, time spent on CA, perceived success in CA, and CA efficiency = success/time spent. The results of this explanatory study are tentative. Major results: Keeping up-to-date is more difficult in specialties with high scatter of information (hypothesis 5). SDI seems to be the only method capable of counteracting scatter (hypotheses 5–7). In contrast, if scatter is low, SDI use decreases CA efficiency (hypothesis 6a); scanning journals, the most prevalent CA method, seems to be sufficient for low-scatter specialties. High scatter does not lead to increased SDI use, in some cases due to perceived difficulty of profile construction (hypothesis 3a). Conclusions: SDI services should concentrate efforts on serving scientists in specialties with high scatter of information by developing systems that are capable of searching across conventional disciplines and specialties, by providing assistance in profile development, and by conducting a marketing campaign directed toward these scientists.

Katherine H. Packer

Papers

The importance of SDI for current awareness in fields with severe scatter of information