An Ontology-based Ranking Model in Search Engines

As the tsunami of data has emerged,search engines have become the most powerful tool for obtaining scattered information on the internet.The traditional search engines return the organized results by using ranking algorithm such as term frequency,link analysis(PageRank algorithm and HITS algorithm)etc.However,these algorithms must combine the keyword frequency to determine the relevance between user’s query and the data in the computer system or internet.Moreover,we expect the search engines could understand users’searching by content meanings rather than literal strings.Semantic Web is an intelligent network and it could understand human’s language more semantically and make the communication easier between human and computers.But,the current technology for the semantic search is hard to apply.Because some meta data should be annotated to each web pages,then the search engine will have the ability to understand the users intend.However,annotate every web page is very time-consuming and leads to inefficiency.So,this study designed an ontology-based approach to improve the current traditional keyword-based search and emulate the effects of semantic search.And let the search engine can understand users more semantically when it gets the knowledge.

People Powered Search Engines:Cyber Witch Hunts or Public Service?

Being too critical, outspoken or engaging in behavior deemed immoral can get you into big trouble in China. And it’s not the authori-ties we’re talking about here. The power of the people has found a new outlet to vent

Design and implementation of semantic search engine Smartch

To integrate reasoning and text retrieval, the architecture of a semantic search engine which includes several kinds of queries is proposed, and the semantic search engine Smartch is designed and implemented. Based on a logical reasoning process and a graphic user-defined process, Smartch provides four kinds of search services. They are basic search, concept search, graphic user-defined query and association relationship search. The experimental results show that compared with the traditional search engine, the recall and precision of Smartch are improved. Graphic user-defined queries can accurately locate the information of user needs. Association relationship search can find complicated relationships between concepts. Smartch can perform some intelligent functions based on ontology inference.

Universal Digital Library—Future research directions

This paper starts with a description of the present status of the Digital Library of India Initiative. As part of this initiative large corpus of scanned text is available in many Indian languages and has stimulated a vast amount of research in Indian language technology briefly described in this paper. Other than the Digital Library of India Initiative which is part of the Million Books to the Web Project initiated by Prof Raj Reddy of Carnegie Mellon University, there are a few more initiatives in India towards taking the heritage of the country to the Web. This paper presents the future directions for the Digital Library of India Initiative both in terms of growing collection and the technical challenges in managing such large collection poses.

Weighted PageRank Algorithm Search Engine Ranking Model for Web Pages

As data grows in size,search engines face new challenges in extracting more relevant content for users’searches.As a result,a number of retrieval and ranking algorithms have been employed to ensure that the results are relevant to the user’s requirements.Unfortunately,most existing indexes and ranking algo-rithms crawl documents and web pages based on a limited set of criteria designed to meet user expectations,making it impossible to deliver exceptionally accurate results.As a result,this study investigates and analyses how search engines work,as well as the elements that contribute to higher ranks.This paper addresses the issue of bias by proposing a new ranking algorithm based on the PageRank(PR)algorithm,which is one of the most widely used page ranking algorithms We pro-pose weighted PageRank(WPR)algorithms to test the relationship between these various measures.The Weighted Page Rank(WPR)model was used in three dis-tinct trials to compare the rankings of documents and pages based on one or more user preferences criteria.Thefindings of utilizing the Weighted Page Rank model showed that using multiple criteria to rankfinal pages is better than using only one,and that some criteria had a greater impact on ranking results than others.

Ontology mapping approach using web search engine

A new mapping approach for automated ontology mapping using web search engines （such as Google） is presented. Based on lexico-syntactic patterns, the hyponymy relationships between ontology concepts can be obtained from the web by search engines and an initial candidate mapping set consisting of ontology concept pairs is generated. According to the concept hierarchies of ontologies, a set of production rules is proposed to delete the concept pairs inconsistent with the ontology semantics from the initial candidate mapping set and add the concept pairs consistent with the ontology semantics to it. Finally, ontology mappings are chosen from the candidate mapping set automatically with a mapping select rule which is based on mutual information. Experimental results show that the F-measure can reach 75% to 100% and it can effectively accomplish the mapping between ontologies.

Scheduling in a Meta Search Engine by Genetic Algorithm

The meta search engines provide service to the users by dispensing the users' requests to the existing search engines. The existing search engines selected by meta search engine determine the searching quality. Because the performance of the existing search engines and the users' requests are changed dynamically, it is not favorable for the fixed search engines to optimize the holistic performance of the meta search engine. This paper applies the genetic algorithm (GA) to realize the scheduling strategy of agent manager in our meta search engine, GSE(general search engine), which can simulate the evolution process of living things more lively and more efficiently. By using GA, the combination of search engines can be optimized and hence the holistic performance of GSE can be improved dramatically.

Agricultural Market Name Geo-Locating System Based on an Administrative Ontology and Web Search Engine

The problem of associating the agricultural market names on web sites with their locations is essential for geographical analysis of the agricultural products. In this paper, an algorithm which employs the administrative ontology and the statistics from the search results were proposed. The experiments with 100 market names collected from web sites were conducted. The experimental results demonstrate that the algorithm proposed obtains satisfactory performance in resolving the problem above, thus the effectiveness of the method is verified.

Research on the User Interest Modeling of Personalized Search Engine

At present, how to enable Search Engine to construct user personal interest model initially, master user＇s personalized information timely and provide personalized services accurately have become the hotspot in the research of Search Engine area. Aiming at the problems of user model＇s construction and combining techniques of manual customization modeling and automatic analytical modeling, a User Interest Model （UIM） is proposed in the paper. On the basis of it, the corresponding establishment and update algorithms of User lnterest Profile （UIP） are presented subsequently. Simulation tests proved that the UIM proposed and corresponding algorithms could enhance the retrieval precision effectively and have superior adaptability.

A Cooperative Schema between Web Sever and Search Engine for Improving Freshness of Web Repository

Because the web is huge and web pages are updated frequently, the index maintained by a search engine has to refresh web pages periodically. This is extremely resource consuming because the search engine needs to crawl the web and download web pages to refresh its index, Based on present technologies of web refreshing, we present a cooperative schema between web server and search engine for maintaining freshness of web repository. The web server provides metadata defined through XML standard to describe web sites. Before updating the web page the crawler visits the meta-data files. If the meta-data indicates that the page is not modified, then the crawler will not update it. So this schema can save bandwidth resource. A primitive model based on the schema is implemented. The cost and efficiency of the schema are analyzed.

A dynamic knowledge base based search engine

Search engines have greatly helped us to find the desired information from the Internet. Most search engines use keywords matching technique. This paper discusses a Dynamic Knowledge Base based Search Engine （DKBSE）, which can expand the user＇s query using the keywords＇ concept or meaning. To do this, the DKBSE needs to construct and maintain the knowledge base dynamically via the system＇s searching results and the user＇s feedback information. The DKBSE expands the user＇s initial query using the knowledge base, and returns the searched information after the expanded query.

A Feedback-Based Web Search Engine

Web search engines are very useful information service tools in the Internet. The current web search engines produce search results relating to the search terms and the actual information collected by them. Since the selections of the search results cannot affect the future ones, they may not cover most people’s interests. In this paper, feedback information produced by the user’s accessing lists will be represented by the rough set and can reconstruct the query string and influence the search results. And thus the search engines can provide self-adaptability. Key words WWW - search engine - query reconstruction - feedback CLC number TP 311. 135.4 Foundation item: Supported by the National Natural Science Fundation of China (60373066). National Grand Fundamental Research 973 Program of China (2002CB31200). Opening Foundation of State Key Laboratory of Software Engineering in Wuhan University, Opening Foundation of Jiangsu Key Laboratory of Computer Information Processing Technology in Soochow UniversityBiography: ZHANG Wei-feng (1975-), male, Ph.D. research direction: artificial intelligence, search engine, data mining, network language.

A Novel Personalized Web Search Model

A novel personalized Web search model is proposed. The new system, as a middleware between a user and a Web search engine, is set up on the client machine. It can learn a user＇s preference implicitly and then generate the user profile automatically. When the user inputs query keywords, the system can automatically generate a few personalized expansion words by computing the term-term associations according to the current user profile, and then these words together with the query keywords are submitted to a popular search engine such as Yahoo or Google. These expansion words help to express accurately the user＇s search intention. The new Web search model can make a common search engine personalized, that is, the search engine can return different search results to different users who input the same keywords. The experimental results show the feasibility and applicability of the presented work.

Study,Analysis and Comparison between Amazon A10 and A11 Search Algorithm

The entirety of Amazon’s sales being powered by Amazon Search,one of the leading e-commerce platforms around the globe.As a result,even slight boosts in appropriateness can have a major impact on profits as well as the shopping experience of millions of users.Throughout the beginning,Amazon’s product search engine was made up of a number of manually adjusted ranking processes that made use of a limited number of input features.Since that time,a significant amount has transpired.Many people overlook the fact that Amazon is a search engine,and even the biggest one for e-commerce.It is indeed time to begin treating Amazon truly as the top e-commerce search engine across the globe because it currently serves 54%of all product queries.In this paper,the authors have considered two most important Amazon search engine algorithms viz.A10 and A11 and comparative study has been discussed.

Search Engine Optimization,Competitive Advantage and Market Performance of Registered Tours and Travel Agencies in Nairobi City County,Kenya

COVID-19 is a devastating pandemic with widespread negative health,social,and economic consequences.Due to drastic changes in the business environment of tour and travel agencies,firms and marketing managers can now use search engine optimization to effectively position themselves.The study’s main goal is to evaluate the effect of search engine optimization on the market performance of registered tours and travel agencies in Nairobi County,Kenya.Kenya’s tourism ministry and state government work hard to improve the business climate for tour and travel companies.Despite the overall positive image,international tourist market growth rates in Kenya have been 3.5 percent slower from 2017 to 2019 compared to previous years.This was further aggregated by the onset of the COVID-19 pandemic in the year 2020,when the growth rate of tours and travel agencies fell by 65%.The study’s main goal is to evaluate the effect of search engine optimization on the market performance of registered tours and travel agencies in Nairobi County,Kenya.This study adopted a positivist philosophy.Both descriptive and explanatory research designs were used.A self-administered semi-structured questionnaire was used to collect data from 324 registered tours and travels agencies picked from and a sample of 179 were used.Data analysis included the development and interpretation of both descriptive and inferential statistics,such as frequencies,mean,percentages,and standard deviation,and was presented using tables and numerical values.The results of regression analysis established that search engine optimization had a positive and significant effect on market performance of the registered tours and travel agencies picked from a sample of 179.The study recommends that agency management ensure that the firm’s website is easily accessible in order to improve agency performance.Using the internet to gain a large market share can assist tours and travel agencies in improving the performance and income of their websites.

Comparison of Websites Employing Search Engine Optimization and Live Data

This study compares websites that take live data into account using search engine optimization(SEO).A series of steps called search engine optimization can help a website rank highly in search engine results.Static websites and dynamic websites are two different types of websites.Static websites must have the necessary expertise in programming compatible with SEO.Whereas in dynamic websites,one can utilize readily available plugins/modules.The fundamental issue of all website holders is the lower level of page rank,congestion,utilization,and exposure of the website on the search engine.Here,the authors have studied the live data of four websites as the real-time data would indicate how the SEO strategy may be applied to website page rank,page difficulty removal,and brand query,etc.It is also necessary to choose relevant keywords on any website.The right keyword might assist to increase the brand query while also lowering the page difficulty both on and off the page.In order to calculate Off-page SEO,On-page SEO,and SEO Difficulty,the authors examined live data in this study and chose four well-known Indian university and institute websites for this study:www.caluniv.ac.in,www.jnu.ac.in,www.iima.ac.in,and www.iitb.ac.in.Using live data and SEO,the authors estimated the Off-page SEO,On-page SEO,and SEO Difficulty.It has been shown that the Off-page SEO of www.caluniv.ac.in is lower than that of www.jnu.ac.in,www.iima.ac.in,and www.iitb.ac.in by 9%,7%,and 7%,respectively.On-page SEO is,in comparison,4%,1%,and 1%more.Every university has continued to keep up its own brand query.Additionally,www.caluniv.ac.in has slightly less SEO Difficulty compared to other websites.The final computed results have been displayed and compared.

Document classification approach by rough-set-based corner classification neural network

A rough set based corner classification neural network, the Rough-CC4, is presented to solve document classification problems such as document representation of different document sizes, document feature selection and document feature encoding. In the Rough-CC4, the documents are described by the equivalent classes of the approximate words. By this method, the dimensions representing the documents can be reduced, which can solve the precision problems caused by the different document sizes and also blur the differences caused by the approximate words. In the Rough-CC4, a binary encoding method is introduced, through which the importance of documents relative to each equivalent class is encoded. By this encoding method, the precision of the Rough-CC4 is improved greatly and the space complexity of the Rough-CC4 is reduced. The Rough-CC4 can be used in automatic classification of documents.

The Theory of Internet Finance

Internet based technologies, such as mobile payments, social networks, search engines and cloud computation, will lead to a paradigm shift in financial sector. Beside indirect financing via commercial banks and direct financing through security markets, a third way to conduct financial activities will emerge, which we call ＂internet finance＇＂ This paper presents a detailed analysis of payment, information processing and resource allocation under internet finance.

The qualitative advantages of quantities of information: bigger is better

Digitization projects should focus on quantity rather than quality. Increasing quantities of information produce qualitatively more valuable services. Online writing and searching are now common, and it is only online reading that is still limiting our use of online books. New interfaces might increase our willingness to read online, which should be encouraged rather than fought, since it represents an increase both the amount of information available and the participation of more people in the writing and exchange of information.

New focused crawling algorithm

Focused carawling is a new research approach of search engine. It restricts information retrieval and provides search service in specific topic area. Focused crawling search algorithm is a key technique of focused crawler which directly affects the search quality. This paper first introduces several traditional topic-specific crawling algorithms, then an inverse link based topic-specific crawling algorithm is put forward. Comparison experiment proves that this algorithm has a good performance in recall, obviously better than traditional Breadth-First and Shark-Search algorithms. The experiment also proves that this algorithm has a good precision.