SemSearch: A Search Engine for the Semantic Web

In this chapter we discuss approaches to find, extract, and structure information from natural language texts on the Web. Such structured information can be expressed and shared using the standard Semantic Web languages and hence be machine interpreted. In this chapter we focus on two tasks in Web information extraction. The first part focuses on mining facts from the Web, while in the second part, we present an approach to collect community-based meta-data. A search engine is used to retrieve potentially relevant texts. From these texts, instances and relations are extracted. The proposed approaches are illustrated using various case-studies, showing that we can reliably extract information from the Web using simple techniques.

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A Review on Semantic Text and Multimedia Retrieval and Recent Trends

International Journal of Multimedia Data Engineering and Management ◽

10.4018/ijmdem.2015010104 ◽

2015 ◽

Vol 6 (1) ◽

pp. 54-74

Author(s):

Oğuzhan Menemencioğlu ◽

İlhami Muharrem Orak

Keyword(s):

Semantic Web ◽

Search Engine ◽

Search Engines ◽

Semantic Search ◽

Multimedia Retrieval ◽

Web Pages ◽

The Face ◽

Recent Trends ◽

New Applications ◽

Machine Readable

Semantic web works on producing machine readable data and aims to deal with large amount of data. The most important tool to access the data which exist in web is the search engine. Traditional search engines are insufficient in the face of the amount of data that consists in the existing web pages. Semantic search engines are extensions to traditional engines and overcome the difficulties faced by them. This paper summarizes semantic web, concept of traditional and semantic search engines and infrastructure. Also semantic search approaches are detailed. A summary of the literature is provided by touching on the trends. In this respect, type of applications and the areas worked for are considered. Based on the data for two different years, trend on these points are analyzed and impacts of changes are discussed. It shows that evaluation on the semantic web continues and new applications and areas are also emerging. Multimedia retrieval is a newly scope of semantic. Hence, multimedia retrieval approaches are discussed. Text and multimedia retrieval is analyzed within semantic search.

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Domain Specific Search Engine Based on Semantic Web

Advances in Intelligent Systems and Computing - Proceedings of the Third International Conference on Soft Computing for Problem Solving ◽

10.1007/978-81-322-1768-8_20 ◽

2014 ◽

pp. 217-224 ◽

Cited By ~ 1

Author(s):

Shruti Kohli ◽

Sonam Arora

Keyword(s):

Semantic Web ◽

Search Engine ◽

Domain Specific ◽

Specific Search

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Search Engine

Semantic Knowledge Management ◽

10.4018/978-1-60566-034-9.ch004 ◽

2011 ◽

pp. 74-100

Author(s):

Eliana Campi ◽

Gianluca Lorenzo

Keyword(s):

Knowledge Management ◽

Information Retrieval ◽

Semantic Web ◽

Knowledge Base ◽

Search Engine ◽

Automatic Classification ◽

Efficient Approach ◽

Search Results ◽

The Creation ◽

F Measure

This chapter presents technologies and approaches for information retrieval in a knowledge base. We intend to show that the use of ontology for domain representation and knowledge search offers a more efficient approach for knowledge management. This approach focuses on the meaning of the word, thus becoming an important element in the building of the Semantic Web. The search based on both keywords and ontology allows more effective information retrieval exploiting the Semantic of the information in a variety of data. We present a method for taxonomy building, annotating, and searching documents with taxonomy concepts. We also describe our experience in the creation of an informal taxonomy, the automatic classification, and the validation of search results with traditional measures, such as precision, recall and f-measure.

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WEBCONTENT VISUALIZER: A VISUALIZATION SYSTEM FOR SEARCH ENGINES IN SEMATIC WEB

International Journal of Information Technology & Decision Making ◽

10.1142/s0219622011004646 ◽

2011 ◽

Vol 10 (05) ◽

pp. 913-931 ◽

Cited By ~ 2

Author(s):

XIANYONG FANG ◽

CHRISTIAN JACQUEMIN ◽

FRÉDÉRIC VERNIER

Keyword(s):

Semantic Web ◽

Search Engine ◽

Search Engines ◽

Web Search ◽

Search Query ◽

Visualization System ◽

Xml Documents ◽

Web Search Engines ◽

New Generation

Since the results from Semantic Web search engines are highly structured XML documents, they cannot be efficiently visualized with traditional explorers. Therefore, the Semantic Web calls for a new generation of search query visualizers that can rely on document metadata. This paper introduces such a visualization system called WebContent Visualizer that is used to display and browse search engine results. The visualization is organized into three levels: (1) Carousels contain documents with the same ranking, (2) carousels are piled into stacks, one for each date, and (3) these stacks are organized along a meta-carousel to display the results for several dates. Carousel stacks are piles of local carousels with increasing radii to visualize the ranks of classes. For document comparison, colored links connect documents between neighboring classes on the basis of shared entities. Based on these techniques, the interface is made of three collaborative components: an inspector window, a visualization panel, and a detailed dialog component. With this architecture, the system is intended to offer an efficient way to explore the results returned by Semantic Web search engines.

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