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The success of the search engine may be our Newtonian paradigm for the Web. It enables us to do so much information discovery that it is difficult to imagine what we cannot do with it.
A keyword choice and analysis approach in SEO is studied to deal with the issues such as low efficiency, poor reliability and instability optimization in artificial SEO processing in this paper. A keyword expansion method is proposed by reversing search engine's related search keywords to meet user's requirements
The search engine, keyword extraction is an important technique. In this paper, aiming at the defects of the traditional keyword extraction algorithm, we proposed an improved weight computation strategy. The experimental results show that, the improved method's results are significantly better results than the
This paper investigates the semantic search performance of search engines. Initially, three keyword-based search engines (Google, Yahoo and Msn) and a semantic search engine (Hakia) were selected. Then, ten queries, from various topics, and four phrases, having different syntax but similar meanings, were determined
KSORD (keyword search over relational database) techniques allow users to obtain information from databases, which is just like using search engines. However, the advanced techniques only realize exact queries, but not for fuzzy queries. The Rocchio algorithm of learning classification is introduced which is made a
Search engines on the Web have popularized the keyword-based search paradigm, while searching in databases users need to know a database schema and a query language. Keyword search techniques on the Web cannot directly be applied to databases because the data on the Internet and database are in different forms. So
Nowadays the existing search engines are always lack of the consideration of personalization. They display the same search results for different users despite their differences in interesting and purpose. In order to solve this problem, this paper introduces a new method of using keyword query series to express the
This paper presents a keyword extraction technique that can be used for tracking topics over time. In our work, keywords are a set of significant words in an article that gives high-level description of its contents to readers. Identifying keywords from a large amount of on-line news data is very useful in that it can
Image annotation becomes increasingly more important as the Web continues to grow. We propose a novel approach to enhancing keyword-based Web-image annotation in folksonomy, where a volunteer user is notified what kind(s) of keywords are necessary, and that keywords have been sufficiently provided by other volunteer
The relevance feedback techniques have been studied in the field of document retrieval, aiming to generate appropriate queries for userspsila information needs. Conventional relevance feedback techniques are performed on document space, while the resultant queries should be represented in keyword space. In this paper
The relevance feedback techniques have been studied in the field of document retrieval, aiming to generate appropriate queries for userspsila information needs.Conventional relevance feedback techniques are performed on document space, while the resultant queries should be represented in keyword space. In this paper
Query-recommendation systems based on inputted queries have become widespread. These services are effective if users cannot input relevant queries. However, the conventional systems do not take into consideration the relevance between recommended queries. This paper proposes a method of obtaining related queries and clustering them by using the history of query frequencies in query logs. We define...
the interfaces of web services, we make operations defined in WSDL files which compose web services as the base units for searching and organize all information of operations and corresponding components as documents, which will facilitate IR-Style keyword searching. In order to improve the precision of searching, we
The problem of automatically extracting the most interesting and relevant keyword phrases in a document has been studied extensively as it is crucial for a number of applications. These applications include contextual advertising, automatic text summarization, and user-centric entity detection systems. All these
suggest the ways that make and renew the ontology, which are related with the keywords that users input in the search engine, automatically for the automatic generation of ontology that is not limited by specific domain. Input keyword and relation keywords become OWL, and the relation among the created OWL is expressed by
keywords from the Web pages. The system first identifies the section of the Web page that contains the multimedia file to be extracted and then extracts it by using clustering techniques and other tools of statistical origin. Experimental results on real-world image sharing Web sites are presented and discussed in this paper
Web pages for search engine. First we describe a scheme based on semantic keywords combined with sentence overlapping, and then show an implemented prototype, with the experimental results that suggest the prototype work well under a proper setting.
This paper presents an attempt to show the efficiency of some search engines in dealing with Arabic keywords. This can be achieved by comparing the number of retrieved pages, retrieving time, and stability (in both the number of retrieved pages and the order for each retrieved page) for each one of the selected 20
Content-based phishing detection extracts keywords from a target Web page, uses these keywords to retrieve the corresponding legitimate site, and detects phishing when the domain of the target page does not match that of the retrieved site. It often misidentifies a legitimate target site as a phishing site, however
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