Incremental relevance feedback

Aalbersberg, IJsbrand Jan

doi:10.1145/133160.133169

Cited by 71 publications

(43 citation statements)

References 14 publications

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“…There has been significant research on text-based profile construction in information retrieval community (e.g., [5,1,7,3]), especially in the framework of TREC [24]. The main emphasis of TREC, however, has always been on the effectiveness of the participating systems, rather than on their efficiency.…”

Section: Related Workmentioning

confidence: 99%

Self-adaptive user profiles for large-scale data delivery

Çetintemel

Franklin

Giles³

Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073)

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Section: Related Workmentioning

confidence: 99%

Self-adaptive user profiles for large-scale data delivery

Çetintemel

Franklin

Giles³

Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073)

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“…Considering that searchers tend to examine a ranked list from top to bottom [10] we feel that this approximation is reasonable. In order to simulate an environment in which users can make mistakes in their relevance judgments, our approach is to build a pool of perceived relevant documents, where this pool consists of non-relevant documents (according to the TREC qrels) that were saved by at least two real users during the original TREC experiments from which we extracted our simulation data.…”

Section: Dynamic Relevance Judgmentsmentioning

confidence: 99%

Synchronous Collaborative Information Retrieval: Techniques and Evaluation

Foley

Smeaton

2009

Lecture Notes in Computer Science

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Abstract. Synchronous Collaborative Information Retrieval refers to systems that support multiple users searching together at the same time in order to satisfy a shared information need. To date most SCIR systems have focussed on providing various awareness tools in order to enable collaborating users to coordinate the search task. However, requiring users to both search and coordinate the group activity may prove too demanding. On the other hand without effective coordination policies the group search may not be effective. In this paper we propose and evaluate novel system-mediated techniques for coordinating a group search. These techniques allow for an effective division of labour across the group whereby each group member can explore a subset of the search space. We also propose and evaluate techniques to support automated sharing of knowledge across searchers in SCIR, through novel collaborative and complementary relevance feedback techniques. In order to evaluate these techniques, we propose a framework for SCIR evaluation based on simulations. To populate these simulations we extract data from TREC interactive search logs. This work represent the first simulations of SCIR to date and the first such use of this TREC data.

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“…For the purposes of the experiments reported in this chapter, our SCIR simulations operate by initiating a relevance feedback operation for a user each time they provide a relevance judgment, thereby returning a new ranked list of documents to the user. This approach is known as Incremental Relevance Feedback, a method first proposed by Aalbersberg (1992). Using the Incremental RF approach, a user is provided with a new ranked list of documents after each relevance judgment, rather than accumulating a series of relevance judgments together and issuing them in batch to the RF process.…”

Section: Requirements Analysismentioning

confidence: 99%

Combining Relevance Information in a Synchronous Collaborative Information Retrieval Environment

Foley

Smeaton

Jones

2009

Collaborative and Social Information Retrieval and Access

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Traditionally information retrieval (IR) research has focussed on a single user interaction modality, where a user searches to satisfy an information need. Recent advances in both Web technologies, such as the sociable Web of Web 2.0, and computer hardware, such as tabletop interface devices, have enabled multiple users to collaborate on many computer-related tasks. Due to these advances there is an increasing need to support two or more users searching together at the same time, in order to satisfy a shared information need, which we refer to as Synchronous Collaborative Information Retrieval. Synchronous Collaborative Information Retrieval (SCIR) represents a significant paradigmatic shift from traditional IR systems. In order to support an effective SCIR search, new techniques are required to coordinate users’ activities. In this chapter we explore the effectiveness of a sharing of knowledge policy on a collaborating group. Sharing of knowledge refers to the process of passing relevance information across users, if one user finds items of relevance to the search task then the group should benefit in the form of improved ranked lists returned to each searcher.In order to evaluate the proposed techniques the authors simulate two users searching together through an incremental feedback system. The simulation assumes that users decide on an initial query with which to begin the collaborative search and proceed through the search by providing relevance judgments to the system and receiving a new ranked list. In order to populate these simulations we extract data from the interaction logs of various experimental IR systems from previous Text REtrieval Conference (TREC) workshops.

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Incremental relevance feedback

Cited by 71 publications

References 14 publications

Self-adaptive user profiles for large-scale data delivery

Self-adaptive user profiles for large-scale data delivery

Synchronous Collaborative Information Retrieval: Techniques and Evaluation

Combining Relevance Information in a Synchronous Collaborative Information Retrieval Environment

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