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Gillitzer, B.: Yewno (2017)
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- Date
- 22. 2.2017 10:16:49
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Vidinli, I.B.; Ozcan, R.: New query suggestion framework and algorithms : a case study for an educational search engine (2016)
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- Abstract
- Query suggestion is generally an integrated part of web search engines. In this study, we first redefine and reduce the query suggestion problem as "comparison of queries". We then propose a general modular framework for query suggestion algorithm development. We also develop new query suggestion algorithms which are used in our proposed framework, exploiting query, session and user features. As a case study, we use query logs of a real educational search engine that targets K-12 students in Turkey. We also exploit educational features (course, grade) in our query suggestion algorithms. We test our framework and algorithms over a set of queries by an experiment and demonstrate a 66-90% statistically significant increase in relevance of query suggestions compared to a baseline method.
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- a
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Pahlevi, S.M.; Kitagawa, H.: Conveying taxonomy context for topic-focused Web search (2005)
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- Abstract
- Introducing context to a user query is effective to improve the search effectiveness. In this article we propose a method employing the taxonomy-based search services such as Web directories to facilitate searches in any Web search interfaces that support Boolean queries. The proposed method enables one to convey current search context an taxonomy of a taxonomy-based search service to the searches conducted with the Web search interfaces. The basic idea is to learn the search context in the form of a Boolean condition that is commonly accepted by many Web search interfaces, and to use the condition to modify the user query before forwarding it to the Web search interfaces. To guarantee that the modified query can always be processed by the Web search interfaces and to make the method adaptive to different user requirements an search result effectiveness, we have developed new fast classification learning algorithms.
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- a
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Scholer, F.; Williams, H.E.; Turpin, A.: Query association surrogates for Web search (2004)
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- Abstract
- Collection sizes, query rates, and the number of users of Web search engines are increasing. Therefore, there is continued demand for innovation in providing search services that meet user information needs. In this article, we propose new techniques to add additional terms to documents with the goal of providing more accurate searches. Our techniques are based an query association, where queries are stored with documents that are highly similar statistically. We show that adding query associations to documents improves the accuracy of Web topic finding searches by up to 7%, and provides an excellent complement to existing supplement techniques for site finding. We conclude that using document surrogates derived from query association is a valuable new technique for accurate Web searching.
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Bhansali, D.; Desai, H.; Deulkar, K.: ¬A study of different ranking approaches for semantic search (2015)
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- Abstract
- Search Engines have become an integral part of our day to day life. Our reliance on search engines increases with every passing day. With the amount of data available on Internet increasing exponentially, it becomes important to develop new methods and tools that help to return results relevant to the queries and reduce the time spent on searching. The results should be diverse but at the same time should return results focused on the queries asked. Relation Based Page Rank [4] algorithms are considered to be the next frontier in improvement of Semantic Web Search. The probability of finding relevance in the search results as posited by the user while entering the query is used to measure the relevance. However, its application is limited by the complexity of determining relation between the terms and assigning explicit meaning to each term. Trust Rank is one of the most widely used ranking algorithms for semantic web search. Few other ranking algorithms like HITS algorithm, PageRank algorithm are also used for Semantic Web Searching. In this paper, we will provide a comparison of few ranking approaches.
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Roy, R.S.; Agarwal, S.; Ganguly, N.; Choudhury, M.: Syntactic complexity of Web search queries through the lenses of language models, networks and users (2016)
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- Abstract
- Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication.
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Schwartz, C.: Web search engines (1998)
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- Abstract
- This reviews looks briefly at the history of WWW search engine development, considers the current state of affairs, and reflects on the future. Networked discovery tools have evolved along with Internet resource availability. WWW search engines display some complexity in their variety, content, resource acquisition strategies, and in the array of tools the deploy to assist users. A small but growing body of evaluation literature, much of it not systematic in nature, indicates that performance effectiveness is difficult to assess in this setting. Significant improvements in general-content search engine retrieval and ranking performance may not be possible, and are probalby not worth the effort, although search engine providers have introduced some rudimentary attempts at personalization, summarization, and query expansion. The shift to distributed search across multitype database systems could extend general networked discovery and retrieval to include smaller resource collections with rich metadata and navigation tools
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Jindal, V.; Bawa, S.; Batra, S.: ¬A review of ranking approaches for semantic search on Web (2014)
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Horch, A.; Kett, H.; Weisbecker, A.: Semantische Suchsysteme für das Internet : Architekturen und Komponenten semantischer Suchmaschinen (2013)
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-
Poynder, R.: Web research engines? (1996)
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