DynaCet: Building Dynamic Faceted Search Systems over Databases

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

doi:10.1109/icde.2009.117

Cited by 29 publications

(19 citation statements)

References 3 publications

(2 reference statements)

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“…Data statistics, including Entropy and Sparsity, were employed to select preferred facets. Roy et al [12] selected facets from database systems by estimating a user cost to locate the desired tuples in the databases. At every step, a user was asked one or more questions about the different facet terms, and the most promising set of facet terms was identified based on the user's response.…”

Section: Facet Mining From Structured Datamentioning

confidence: 99%

DF-Miner: Domain-specific facet mining by leveraging the hyperlink structure of Wikipedia

Wei

Zheng

et al. 2015

Knowledge-Based Systems

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Section: Facet Mining From Structured Datamentioning

confidence: 99%

DF-Miner: Domain-specific facet mining by leveraging the hyperlink structure of Wikipedia

Wei

Zheng

et al. 2015

Knowledge-Based Systems

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“…For structured data, the main task of facet term extraction is to select facet terms from attributes of database. Roy et al [19] presented a method, DynaCet -a domain independent system that provides effective minimum-effort based dynamic faceted search solutions over enterprise databases. At every step, a user is asked one or more questions about the different facet terms, and the most promising set of facet terms is identified based on the user's response.…”

Section: Facet Extraction Of Structured Datamentioning

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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“…But for the database query form, a database query is a structured relational query, not just a set of terms. Dynamic Faceted Search: Dynamic faceted search is a type of search engines where relevant facets are presented for the users according to their navigation paths [29] [23]. Dynamic faceted search engines are similar to our dynamic query forms if we only consider Selection components in a query.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Query Forms for Database Queries

Tang

Jiang

et al. 2014

IEEE Trans. Knowl. Data Eng.

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Abstract-Modern scientific databases and web databases maintain large and heterogeneous data. These real-world databases contain over hundreds or even thousands of relations and attributes. Traditional predefined query forms are not able to satisfy various ad-hoc queries from users on those databases. This paper proposes DQF, a novel database query form interface, which is able to dynamically generate query forms. The essence of DQF is to capture a user's preference and rank query form components, assisting him/her to make decisions. The generation of a query form is an iterative process and is guided by the user. At each iteration, the system automatically generates ranking lists of form components and the user then adds the desired form components into the query form. The ranking of form components is based on the captured user preference. A user can also fill the query form and submit queries to view the query result at each iteration. In this way, a query form could be dynamically refined till the user satisfies with the query results. We utilize the expected F-measure for measuring the goodness of a query form. A probabilistic model is developed for estimating the goodness of a query form in DQF. Our experimental evaluation and user study demonstrate the effectiveness and efficiency of the system.

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DynaCet: Building Dynamic Faceted Search Systems over Databases

Cited by 29 publications

References 3 publications

DF-Miner: Domain-specific facet mining by leveraging the hyperlink structure of Wikipedia

DF-Miner: Domain-specific facet mining by leveraging the hyperlink structure of Wikipedia

Survey on Query Facets Mining Approaches

Dynamic Query Forms for Database Queries

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