Minimum-effort driven dynamic faceted search in structured databases

Roy, Senjuti Basu; Wang, Haidong; Das, Gautam; Nambiar, Ullas; Mohania, Mukesh

doi:10.1145/1458082.1458088

Cited by 55 publications

(16 citation statements)

References 14 publications

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“…Query Reformulation for Structured Databases: The closest related works are interactive optimization-based approaches studied for the many-answers problem, most notably [6,18,20], where given an initial query that returns a large number of answers, the objective is to design an effective drill-down strategy to help the user find acceptable results with minimum effort. We solve the complementary problem, where we have an empty answer and we need to relax the query condition to get a non-empty one.…”

Section: Related Workmentioning

confidence: 99%

“…However, in the case of a naive user who is unable to provide a good ranking function, there have been many efforts to develop suitable system-generated ranking functions, both by IR [5] and database [1,10,11] researchers. At the same time, it has also been recognized [6,14] that the rank-retrieval based approach has an inherent limitation for naive users -it is not an interactive process, and if the user does not like the returned results, it is not easy to determine how the system-generated ranking function should be changed. In this context, interactive approaches such as query reformulation are popular alternatives.…”

Section: Related Workmentioning

confidence: 99%

“…We provide a detailed discus- sion of related work in Section 8. Optimization-based interactive approaches have been proposed for the many-answers problem [6,18,20], however these papers only consider one narrow optimization goal, that of minimizing user effort. Moreover, we note that there is a fundamental asymmetry between the empty-answer and many-answers problems that precludes a straightforward adaptation of previous optimization-based query tightening techniques to query relaxation.…”

Section: Introductionmentioning

confidence: 99%

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A probabilistic optimization framework for the empty-answer problem

et al. 2013

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We propose a principled optimization-based interactive query relaxation framework for queries that return no answers. Given an initial query that returns an empty answer set, our framework dynamically computes and suggests alternative queries with less conditions than those the user has initially requested, in order to help the user arrive at a query with a non-empty answer, or at a query for which no matter how many additional conditions are ignored, the answer will still be empty. Our proposed approach for suggesting query relaxations is driven by a novel probabilistic framework based on optimizing a wide variety of application-dependent objective functions. We describe optimal and approximate solutions of different optimization problems using the framework. We analyze these solutions, experimentally verify their efficiency and effectiveness, and illustrate their advantage over the existing approaches.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A probabilistic optimization framework for the empty-answer problem

et al. 2013

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“…It follows that IOS can be used for accelerating the performance of multifaceted browsing interfaces [4,3,6].…”

Section: Applications Of Iosmentioning

confidence: 99%

Exploiting Available Memory and Disk for Scalable Instant Overview Search

Fafalios

Tzitzikas

2011

Lecture Notes in Computer Science

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Abstract. Search-As-You-Type (or Instant Search) is a recently introduced functionality which shows predictive results while the user types a query letter by letter. In this paper we generalize and propose an extension of this technique which apart from showing on-the-fly the first page of results, it shows various other kinds of information, e.g. the outcome of results clustering techniques, or metadata-based groupings of the results. Although this functionality is more informative than the classic search-as-you type, since it combines Autocompletion, Search-AsYou-Type, and Results Clustering, the provision of real-time interaction is more challenging. To tackle this issue we propose an approach based on pre-computed information and we comparatively evaluate various index structures for making real-time interaction feasible, even if the size of the available memory space is limited. This comparison reveals the memory/performance trade-off and allows deciding which index structure to use according to the available main memory and desired performance. Furthermore we show that an incremental algorithm can be used to keep the index structure fresh.

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“…8. Optimization-based interactive approaches have been proposed for the many-answers problem [7,30,32]; however, these papers only consider one narrow optimization goal, that of minimizing user effort. We note that there is a fundamental asymmetry between the empty-answer and many-answers problems that precludes a straightforward adaptation of previous optimization-based query tightening techniques to query relaxation.…”

Section: Introductionmentioning

confidence: 99%

A holistic and principled approach for the empty-answer problem

et al. 2016

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We propose a principled optimization-based interactive query relaxation framework for queries that return no answers. Given an initial query that returns an empty-answer set, our framework dynamically computes and suggests alternative queries with fewer conditions than those the user has initially requested, in order to help the user arrive at a query with a non-empty-answer, or at a query for which no matter how many additional conditions are ignored, the answer will still be empty. Our proposed approach for suggesting query relaxations is driven by a novel probabilistic framework based on optimizing a wide variety of application-dependent objective functions. We describe optimal and approximate solutions of different optimization problems using the framework. Moreover, we discuss two important extensions to the base framework: the specification of a minimum size on the The work was primarily done while D. Mottin and A. Marascu were at the University of Trento. number of results returned by a relaxed query and the possibility of proposing multiple conditions at the same time. We analyze the proposed solutions, experimentally verify their efficiency and effectiveness, and illustrate their advantages over the existing approaches.

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Minimum-effort driven dynamic faceted search in structured databases

Cited by 55 publications

References 14 publications

A probabilistic optimization framework for the empty-answer problem

A probabilistic optimization framework for the empty-answer problem

Exploiting Available Memory and Disk for Scalable Instant Overview Search

A holistic and principled approach for the empty-answer problem

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