The study of key techniques in intelligent XML search engine

Author(s):  
Fang Yuan ◽  
Ya-Nan Hao ◽  
Ge Yu
Author(s):  
Kamal Taha ◽  
Ramez Elmasri

With the emergence of the World Wide Web, business’ databases are increasingly being queried directly by customers. The customers may not be aware of the exact structure of the underlying data, and might have never learned a query language that enables them to issue structured queries. Some of the employees who query the databases may also not be aware of the structure of the data, but they are likely to be aware of some labels of elements containing the data. There is a need for a dual search engine that accommodates both business employees and customers. We propose in this chapter an XML search engine called SEEC, which accepts Keyword-Based queries (which can be used for answering customers’ queries) and Loosely Structured queries (which can be used for answering employees’ queries). We proposed previously a stand-alone Loosely Structured search engine called OOXSearch (Taha & Elmasri, 2007). SEEC integrates OOXSearch with a Keyword-Based search engine and uses novel search techniques. It is built on top of an XQuery search engine (Katz, 2005). SEEC was evaluated experimentally and compared with three recently proposed systems: XSEarch (Cohen & Mamou & Sagiv, 2003), Schema Free XQuery (Li & Yu & Jagadish, 2004), and XKSearch (Xu & Papakonstantinou, 2005). The results showed marked improvement.


2013 ◽  
Vol 303-306 ◽  
pp. 2416-2424
Author(s):  
Hu Yin ◽  
Yun Fei Lv ◽  
Wei Wei Wang

We discuss some key techniques associated with integrating user social data recommendation into entity search engine, which can provide entity search engine more accurate information and make up for automatically fetching information on Web. The goal of social data recommendation is to make search engine become a content provider, and solve some challenges that traditional architecture of search engine has faced with, such as limited resources, accurate search, etc. To this end, we describe the storage format of the user social recommended data and submission methods for them. For the purpose of fusing this structural information into entity search engine, we present formal definitions related to Web entity fusion, and give several important fusion operators, and discuss their properties. Finally, we propose a Web entity fusion algorithm, which exploits some techniques related to natural language processing such as sentence similarity computation and sentence fusion. Our experimental results show that the proposed algorithms are effective.


2013 ◽  
Vol 651 ◽  
pp. 906-909
Author(s):  
Ling Qiu ◽  
Zheng Xi Wei

Content-based image search is an urgent problem as the next generation of search engines. This paper firstly analyzes and discusses its main features and key techniques, and then presents a designs method of image search engine based on image content. Next, we give a detailed elaboration about the main function modules and introduce the testing process. By using data filtering technology and ELFHash algorithms, the search time-consume is less than 1 second. The testing results finally prove the overall performance of our image search engine is excellent and achieves the desired design requirements.


2003 ◽  
Vol 62 (2) ◽  
pp. 121-129 ◽  
Author(s):  
Astrid Schütz ◽  
Franz Machilek

Research on personal home pages is still rare. Many studies to date are exploratory, and the problem of drawing a sample that reflects the variety of existing home pages has not yet been solved. The present paper discusses sampling strategies and suggests a strategy based on the results retrieved by a search engine. This approach is used to draw a sample of 229 personal home pages that portray private identities. Findings on age and sex of the owners and elements characterizing the sites are reported.


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