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.

Application of a Web Search Engine in Translating Business Terms in English-Chinese Dictionaries

Web search engines are important tools for lexicography.This paper takes translation of business terms("e-commerce"and"e-business")as an example to illustrate the application of web search engines in English-Chinese dictionary translation,including the methods of(1)finding the potential Chinese equivalents of the English business terms,and(2)selecting typical and proper Chinese equivalents in accordance with the frequencies and the meanings of the English business terms respectively.

Website Search Engine Optimization: Geographical and Cultural Point of View

The concept of Webpage visibility is usually linked to search engine optimization (SEO), and it is based on global in-link metric [1]. SEO is the process of designing Webpages to optimize its potential to rank high on search engines, preferably on the first page of the results page. The purpose of this research study is to analyze the influence of local geographical area, in terms of cultural values, and the effect of local society keywords in increasing Website visibility. Websites were analyzed by accessing the source code of their homepages through Google Chrome browser. Statistical analysis methods were selected to assess and analyze the results of the SEO and search engine visibility (SEV). The results obtained suggest that the development of Web indicators to be included should consider a local idea of visibility, and consider a certain geographical context. The geographical region that the researchers are considering in this research is the Hashemite kingdom of Jordan (HKJ). The results obtained also suggest that the use of social culture keywords leads to increase the Website visibility in search engines as well as localizes the search area such as google.jo, which localizes the search for HKJ.

基于Hash算法实现搜索引擎中重复WEB页面的消除

搜索引擎已经成为互联网用户进入网络的一个重要入口。但目前搜索引擎的结果还存在着许多有待改进的地方。本文从搜索引擎返回结果中存在的重复页面入手,解决如何消除重复页面,并对其将来的发展进行了进一步探讨。

Web挖掘技术在搜索引擎中的应用

As a new knowledge mining means,Web mining provides a new solution for the utilization of Web information resources This article describes the application of Web mining technologies in search engines,and discusses how to mine the latest technologies for search engines so as to improve their retrieving

Web搜索中的数据挖掘技术研究

WWW已经成为世界上是大的分布式信息系统,如何快速有效地搜索用户所需的资源一直是研究热点。Web挖掘也已经成为数据挖掘中相对成熟的一个分支。本文针对Web资源搜索中利用的相关Web挖掘技术做一个综述。文章首先对目前流行的Web内容挖掘方面的常用技术进行了研究分析,然后着重研究了Web结构挖掘技术,介绍并评价了多种算法模型。接着介绍了用户使用的挖掘,并提出了Web内容挖掘技术,结构挖掘技术和用户使用挖掘相结合,应用于开发智能型搜索引擎的趋势。

A geospatial search engine for discovering multi-format geospatial data across the web

The volume of publically available geospatial data on the web is rapidly increasing due to advances in server-based technologies and the ease at which data can now be created.However,challenges remain with connecting individuals searching for geospatial data with servers and websites where such data exist.The objective of this paper is to present a publically available Geospatial Search Engine(GSE)that utilizes a web crawler built on top of the Google search engine in order to search the web for geospatial data.The crawler seeding mechanism combines search terms entered by users with predefined keywords that identify geospatial data services.A procedure runs daily to update map server layers and metadata,and to eliminate servers that go offline.The GSE supports Web Map Services,ArcGIS services,and websites that have geospatial data for download.We applied the GSE to search for all available geospatial services under these formats and provide search results including the spatial distribution of all obtained services.While enhancements to our GSE and to web crawler technology in general lie ahead,our work represents an important step toward realizing the potential of a publically accessible tool for discovering the global availability of geospatial data.

Web search engine:characteristics of user behaviors and their implication

In this paper, first studied are the distribution characteristics of user behaviors based on log data from a massive web search engine. Analysis shows that stochastic distribution of user queries accords with the characteristics of power-law function and exhibits strong similarity, and the user' s queries and clicked URLs present dramatic locality, which implies that query cache and 'hot click' cache can be employed to improve system performance. Then three typical cache replacement policies are compared, including LRU, FIFO, and LFU with attenuation. In addition, the distribution character-istics of web information are also analyzed, which demonstrates that the link popularity and replica pop-ularity of a URL have positive influence on its importance. Finally, variance between the link popularity and user popularity, and variance between replica popularity and user popularity are analyzed, which give us some important insight that helps us improve the ranking algorithms in a search engine.

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.

一种N层体系结构下的Web挖掘应用

W eb应用的深入使N层体系结构的系统逐渐被广泛使用,同时网上的海量信息也为W eb挖掘提供了一个广阔的应用领域。本文针对在N层体系结构中应用W eb挖掘技术进行了研究;包括在N层体系结构中实现网站用户访问分析、智能搜索引擎和个性化推荐等;对数据源的处理和转换、数据仓库的建立和使用以及业务处理过程的改进等都进行了论述。

基于图匹配的Web实体抽取算法研究

现今Web中存在大量缺失、不一致及不精确的数据,而传统的搜索引擎只能根据关键词返回文档片段,无法直接获取目标实体。提出一种新的基于图匹配的实体抽取算法GMEE(Graph Matching Based Entity Extraction),首先将片段按词语分割,进行实体的初步筛选;然后根据各实体之间的结构和语义关系建立“加权语义实体关联图”;最后利用“最大公共子图匹配”策略抽取目标实体。实验结果表明,提出的算法在不需要大量参数训练及传递的情况下,能够对抽取的实体集进行有效的精简,既保证了召回率、准确率,又提高了抽取过程的可解释性。

基于语义Web服务的分布式服装搜索引擎系统设计

从电子商务环境下服装供应链管理的需求出发,分析了目前服装搜索引擎存在的问题,提出了基于语义Web服务的分布式服装商品搜索引擎系统模型,并讨论了它的体系结构。介绍了基于Ontology Web Language(OWL)的服装本体设计模型及其语义描述方法。分析了服装搜索引擎的基本功能及分布式环境下的Web Services(WS)合成。理论分析和实例原型说明了基于服装语义树的搜索引擎多关键词搜索效率明显高于全文搜索引擎。

基于DC元数据的Web网络搜索引擎系统设计

传统搜索引擎通常靠抓取全文关键词进行分析,由此带来三大缺陷:缺乏语义描述导致查准率低;检索结果冗余模糊导致检索效率低;检索途径不足.基于DC元数据描述网络资源的优越性,课题组设计了一个基于DC元数据的网络搜索引擎系统DCSE,力图克服传统搜索引擎的上述缺陷.DCSE系统自动抓取含DC描述的Web网页,把DC描述信息存入到数据库,排序索引后提供用户检索.检索界面设计成以15个DC元素为检索项的多项逻辑组合检索,检索结果以各DC元素的描述内容来显示,如标题、创建者、描述、日期等.用户通过多项组合检索提高查准率,并通过清晰的结果显示对所需信息做出快速判断、选择,从而达到提高检索效率的目的.

Web信息检索的技术分析与发展策略研究

随着 Web 的不断发展,对高速而有效的信息检索系统需求日渐迫切。本文对信息检索的核心技术——搜索引擎进行了分析,找出其表现不佳的原因。在综合考虑当前的搜索引擎发展趋势的基础上,提出了基于语义的 Web社区的发展策略。

基于访问内容类型统计的Web Robot检测算法

随着搜索引擎的广泛使用,由此而引起的网络机器人(Web Robot)对于Web站点的访问所产生的影响必须引起重视。该文分析了网络机器人的访问行为特点,提出了一个基于访问内容类型统计的检测算法。经实验验证,该算法可以有效地检测未知的和不遵守网络机器人排斥标准的Robot。

Web环境下分布式信息检索模式

本文介绍了元搜索引擎、Z39.5 0协议、XML 和 Web服务的基本知识 ,在此基础上探讨了四种分布式信息检索模式的基本原理 ,并对四种模式作了简单的评价。

基于WEB的数据挖掘研究综述

运用数据挖掘技术进行Web数据挖掘成为数据分析领域中的一个重要研究热点,与传统数据相比较,Web数据具有结构复杂、形式多样与内容广泛等特点,且用户对其需求亦是五花八门的,这对数据分析领域提出了更大的挑战.基于为研究Web数据挖掘提供参考,将Web数据挖掘粗略地分为三类:内容挖掘、结构挖掘和使用挖掘,并分别进行了综述,然后根据当前的应用现状分析了这一研究领域的几个研究方向.

主题精选算法中Web邻域图的构造

给出了为主题精选算法(如HITS)构造Web邻域图的方法和实用系统。该系统基于Web搜索引擎(AltaVista),使用额外的Visual C++软件模块构造一个查询特定的邻域图,并将图节点和边信息存储于数据库中以供超链分析使用。Web环境的实验表明该邻域图构造方法是可行的,邻域图构造系统是可靠的。

基于Web的EI检索系统

介绍美国 Elsevier工程信息公司出版的《工程索引》( EI)及其系列数据库和检索平台的最新概况 ,重点讨论 EI的网络版 ,即 EI Compendex Web数据库的特点。