外文翻译---本体论语义搜索引擎模型(编辑修改稿)

外文翻译---本体论语义搜索引擎模型(编辑修改稿)内容摘要：

译文成绩 （百分制） ： 指导教师签名： 年 月 日 18 Prototype of Semantic Search Engine Using Ontology Ahmad Maziz Esa, Shakirah Mohd Taib, Nguyen Thi Hong Computer Information Sciences Universiti Teknologi Petronas Tronoh, Perak , , Abstract— In this paper we discuss the fundamental problem of information retrieval on the Web. Information on the Web is not semantically categorized and stored. This research focuses on applying semantic capabilities using ontology on search engine. By using ontology, search engine can search keywords that are conceptually linked instead of just similarity of the words used. This paper also provides in depth description of the architecture design of our proposed modified search engine. This paper describes how the mechanism is designed so that the search engine can extract information stored based on the ontology and present a semantically linked search results. The benefits and future improvements are also discussed. Keywordsponent。 search engine, semantic, information retrieval, ontology. INTRODUCTION The Web at its infancy was a static page which allows users to open and read the contents of 19 the Web pages. There was only a oneway interaction between the users and the Web. As the technology advances, Webenabled devices were getting cheaper and more ubiquitous. More and more people are able to access the Web and utilize the wealth of information in it. This triggered a paradigm shift in Web usage and the way people interact with the Web. Experts and laymen coined this shifting in Web interaction as Web . A Web site enables users to interact with the Web more interactively with still and moving graphics as well as sound [1]. Users were also able to publish their contents for the consumption of other users. It gave way to the birth of Web technologies such as Friendster [2], Youtube [3], Blogger [4] and Facebook [5]. It was an age of ‚content by the users for the users‛. Content creation were not limited to just an organization but also to anyone who has access to the Inter. As envisioned by Tim Berners Lee in his book titled Weaving the Web [6], the Web will implement semantic properties in its collection of Web pages which will understand the words and terms human used. The large amount of information on the Web can be retrieved using a search engine. Since Web , many search engines were developed and been mercialized. These search engines such as Google[7], AskJeeves[8], Yahoo![9], and Lycos[10] were among the search engines that were dominating at its time. Search engines help users by indexing all the information on the Web and make it easy and quickly retrievable for the users. Early search engines were not a search engine at all. Instead it was a directory which contained indexed information which were indexed manually by the directory provider. It was Google who among the first that implement automate indexing and crawling mechanism which enables the search engine to automatically crawl Web pages and indexed the retrieved Web pages for users to search [11]. Google uses page rank by keeping track the number of ining links and links linked to other pages. The more links linked to a page the more 20 credible the page is, thus will be ranked higher than the other. All these were being puted using mathematical algorithms by calculating the term frequency and inverted term frequency. Data crawled and collected were stored in an inverted database which enables the search engine to locate which terms were stored in which document or links. There is no doubt that the collection of information on the Web is increasing. As for now, with the current search engine which utilizes on mathematical algorithms will be able to cope. As the collection of the information bees larger, it will dilute the accuracy of conventional search engine making it less accurate and less precise. The dilution of the result accuracy will be further aggravated as the collection of information grows rapidly. This work aims to tackle the problem from a different angle. Instead of trying to preserve the accuracy of search engine by relying on machines speed and processing power to enable the usage of more sophisticated mathematical algorithms, this work will explore semantic utilization in search engine. By implementing semantic mechanism in search engine, it will enable information to be related to each other conceptually. This will give the information indexed with the semantic value which can improve information retrieval. Major contributions of this work are basically the analysis of semantic search engine and the development of semantic search engine prototype which enables user to have more accurate search semantically. Section 2 describes related works done. Section 3 describes the methodology used to analyze and develop a semantic search engine. Section 4 describes the architecture and algorithm used in order to provide semantic mechanism for the search engine. Section 5 concludes the paper and finally section 6 describes future improvements to this work. RELATED WORKS 21 Currently, a general purpose ‚semantic‛ search engine had been developed. The search engine can be accessed at . However, most of the mechanism used in the search engine were patented and focused on mercial use. As quoted by Tim Berners Lee [6], ‚I mention patents in passing, but they are a great stumbling block for Web development‛. All the technologies used in Hakia[12] were patented and therefore are trade secret. This prevent academic circle to study intricate workings of the search engine for future improvement and other applications. Many search engines have been developed throughout the years. One of the most dominant was Google[7]. Many t。