Work

Data Mining Techniques for Mining Query Logs in Web Search Engines

Year: 2017

Type: article

Abstract: The Web is the biggest repository of documents humans have ever built. Even more, it is increasingly growing in size every day. Users rely on Web search engines (WSEs) for finding information on the Web. By submitting a textual query expressing their information need, WSE users obtain a list of documents that are highly relevant to the query. Moreover, WSEs store such huge amount of users activities in query logs. Query log mining is the set of techniques aiming at extracting valuable knowledge from query logs. This knowledge represents one of the most used ways of enhancing the users search experience. The primary focus of this work is on introducing the data mining techniques for mining query logs in web search engines and showing how search engines applications may benefit from this mining.

Source: HAL

Authors: Al-Hegami, Ahmed, Sultan, Al-Omaisi, Hussein

Institutions: Sana'a University, Alandalus University For Science & Technology

Language: English

Topic: Information Retrieval and Search Behavior

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W3011199318

FWCI: 0.677

Cites:

Cited by: 2

Related to: 10