Extracting query facets from search results

Kong, Weize; Allan, James

doi:10.1145/2484028.2484097

Cited by 59 publications

(52 citation statements)

References 33 publications

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“…To cope with this challenge, in this chapter, we propose an alternative solution, called query facet extraction (Kong and Allan, 2013), which extracts facets for queries (called query facets) from their web search results. For example, when users search with the query "baggage allowance", the system might extract query facets like airlines, {"Delta", "JetBlue", "AA", ...}, travel classes, {"first", "business", "economy"}, and flight types, {"international ", "domestic"}.…”

Section: Discussionmentioning

confidence: 99%

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Extending Faceted Search to the Open-Domain Web

Kong

2016

SIGIR Forum

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To mom and dad ACKNOWLEDGMENTSI would like to express my deepest thanks to my advisor, James Allan, for his immense support and guidance throughout my PhD study. I especially thank James for giving me lots of freedom in research, which makes the years of PhD study a very enjoyable journey. In conventional faceted search, facets are generated in advance for an entire corpus either manually or semi-automatically, and then recommended for particular queries in most of the previous work. However, this approach is difficult to extend to the entire web due to the web's large and heterogeneous nature. We instead propose a querydependent approach, which extracts facets for queries from their web search results.We further improve our facet generation model under a more practical scenario, where users care more about precision of presented facets than recall.The dominant facet feedback method in conventional faceted search is Boolean filtering, which filters search results by users' selections on facets. However, our investigation shows Boolean filtering is too strict when extended to the open-domain setting. Thus, we propose soft ranking models for Faceted Web Search, which expand original queries with users' selections on facets to re-rank search results. Our experiments show that the soft ranking models are more effective than Boolean filtering models for Faceted Web Search.To evaluate Faceted Web Search, we propose both intrinsic evaluation, which evaluates facet generation on its own, and extrinsic evaluation, which evaluates an entire Faceted Web Search system by its utility in assisting search clarification. We also design a method for building reusable test collections for such evaluations. Our experiments show that using the Faceted Web Search interface can significantly improve the original ranking if allowed sufficient time for user feedback on facets.viii

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Section: Discussionmentioning

confidence: 99%

“…To combine the two evaluation aspects, we design a new measure called P RF α,β (Kong and Allan, 2013). P RF α,β combines T P , T R and P F using weighted harmonic mean, where T P , T R and P F are precision and recall for facet terms, and the F1 measure for facet term clustering.…”

Section: Introductionmentioning

confidence: 99%

Extending Faceted Search to the Open-Domain Web

Kong

2016

SIGIR Forum

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“…Weize Kong and James Allan describes a method [7] for extracting query facets from search results. Web search queries are often ambiguous or multi-faceted, which makes a simple ranked list of results insufficient.…”

Section: Literature Reviewmentioning

confidence: 99%

A Survey on Mining Aspects for Queries

Padmanabhan¹,

D²

2017

International Journal of Advanced Research in Computer and Comm

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Abstract:There is a problem of finding query facets or angles that is a particular aspect or feature of something which are multiple groups of words or phrases that explain and summarize th content covered by a query. Query facets provide interesting and useful knowledge about a query and thus can be used to improve search experiences in many ways. First, we can display query facets together with the original search results in an appropriate way. Second, query facets may provide direct information or instant answers that users are seeking. Third, query facets may also be used to improve the diversity of the ten blue links. It is an assumption that the important aspects of a query are usually presented and repeated in the query's top retrieved documents in the style of lists, and query facets can be mined out by aggregating these significant lists. This can be solved by automatically mine query facets by extracting and grouping frequent lists from free text, HTML tags, and repeat regions within top search results. Then a large number of lists do exist and useful query angles can be mined.

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“…A query facet is defined as a set of coordinate terms i.e. terms that share a semantic relationship by being grouped under a more general hypernym ("is a" relationship) [2]. For example, Facets for the query "watches", shown in Fig.…”

Section: Key Conceptsmentioning

confidence: 99%

“…Faceted search is similar to query facet mining. Both of them use sets of coordinate terms to represent different facets of a query [2]. But most existing works for faceted search and query facets extraction are built on a specific domain or predefined categories.…”

Section: Faceted Search and Query Facets Miningmentioning

confidence: 99%

Survey on Query Facets Mining Approaches

2017

IJSR

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Important features of a query are generally presented and repeated in the top retrieved documents in the style of lists. Query facets can be extracted by collecting these significant lists. Query facets may provide direct information or instant answers that users are seeking i.e. user can select a particular facet item which he found relevant to his search need. So the list format style is much more user friendly than displaying searches sentence wise. The scope of this survey is limited to get search results of a query in list format i.e. facets. Previously there has been lot of work done for retrieving more relevant data to users in order to meet their information needs thus improving performance of search engines. Search engine provide the platform for users to describe their information need more clearly by using query facets mining. Different approaches for extraction of query facets from web search results to assist information finding for queries are discussed along with similar techniques used earlier for information retrieval of queries. Query facets represents interesting facets of a query using groups of semantically related terms extracted from search results. This paper reviews techniques that represents interesting facets of a query using groups of semantically related terms extracted from search results along with approaches that are similar to query facets mining .

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Extracting query facets from search results

Cited by 59 publications

References 33 publications

Extending Faceted Search to the Open-Domain Web

Extending Faceted Search to the Open-Domain Web

A Survey on Mining Aspects for Queries

Survey on Query Facets Mining Approaches

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