A contingency model of computer and Internet self-efficacy

Information system researchers have recently devoted considerable attention to the concept of computer self-efficacy in order to understand computer user behavior and system use. This article reports on the development and examination of a contingency model of computer and Internet self-efficacy. User attitude and computer anxiety were assumed to influence the development of computer and Internet self-efficacy. Measures of user attitude, computer anxiety, computer self-efficacy, and Internet self-efficacy were used in a university environment to collect 347 responses at both the beginning and end of an introductory computer course. Results suggested that training significantly improved computer and Internet self-efficacy. Respondents with ‘favorable’ attitudes toward computers improved their self-efficacy significantly more than respondents with ‘unfavorable’ attitudes. Respondents with ‘low’ computer anxiety improved their self-efficacy significantly more than respondents with ‘high’ computer anxiety. The interaction effect between attitude and anxiety was significant for computer self-efficacy scores but not for Internet self-efficacy scores. The implications of these findings are discussed.     

A statistical method for estimating the usefulness of text databases

Searching desired data on the Internet is one of the most common ways the Internet is used. No single search engine is capable of searching all data on the Internet. The approach that provides an interface for invoking multiple search engines for each user query has the potential to satisfy more users. When the number of search engines under the interface is large, invoking all search engines for each query is often not cost effective because it creates unnecessary network traffic by sending the query to a large number of useless search engines and searching these useless search engines wastes local resources. The problem can be overcome if the usefulness of every search engine with respect to each query can be predicted. We present a statistical method to estimate the usefulness of a search engine for any given query. For a given query, the usefulness of a search engine in this paper is defined to be a combination of the number of documents in the search engine that are sufficiently similar to the query and the average similarity of these documents. Experimental results indicate that our estimation method is much more accurate than existing methods.     

Supporting metasearch with XSL

Metasearch engines offer better coverage and are more fault-tolerant and expandable than single search engines. A metasearch engine is required to post queries with and obtain retrieval results from several other Internet search engines. In this paper, we describe the use of the extensible style language (XSL) to support metasearches. We show how XSL can transform a query, expressed in XML, into different forms for different search engines. We show how the retrieval results could be transformed into a standard format so that the metasearch engine can interpret the retrieved data, filtering the irrelevant information (e.g. advertisement). The proposed structure treats the metasearch engine and the individual search engines as separate modules with a clearly defined communication structure through XSL. Thus, the system is more extensible than coding the structure and syntactic transformation processes. It allows other new search engines to be included just through plug-and-play, requiring only that the new transformation of XML for this search engine be included in the XSL.     

An investigation of user attitudes toward search engines as an information retrieval tool

After the Internet has gained great popularity at homes and schools, there is much information on the Web. Today, one of the primary uses of the Internet is information retrieval from search engines. The main purpose of the current study is to develop and examine an individual attitude model towards search engines as a tool for retrieving information. This model integrates individual computer experience with perceptions. In addition, it also combines perception theories, such as technology acceptance model (TAM) and motivation, in order to understand individual attitudes toward search engines. The results show that individual computer experience, quality of search systems, motivation, and perceptions of technology acceptance are all key factors that affect individual feelings to use search engines as an information retrieval tool.     

Reducing Query Latencies in Web Search Using Fine-Grained Parallelism

Semantic Web search is a new application of recent advances in information retrieval (IR), natural language processing, artificial intelligence, and other fields. The Powerset group in Microsoft develops a semantic search engine that aims to answer queries not only by matching keywords, but by actually matching meaning in queries to meaning in Web documents. Compared to typical keyword search, semantic search can pose additional engineering challenges for the back-end and infrastructure designs. Of these, the main challenge addressed in this paper is how to lower query latencies to acceptable, interactive levels. Index-based semantic search requires more data processing, such as numerous synonyms, hypernyms, multiple linguistic readings, and other semantic information, both on queries and in the index. In addition, some of the algorithms can be super-linear, such as matching co-references across a document. Consequently, many semantic queries can run significantly slower than the same keyword query. Users, however, have grown to expect Web search engines to provide near-instantaneous results, and a slow search engine could be deemed unusable even if it provides highly relevant results. It is therefore imperative for any search engine to meet its users’ interactivity expectations, or risk losing them. Our approach to tackle this challenge is to exploit data parallelism in slow search queries to reduce their latency in multi-core systems. Although all search engines are designed to exploit parallelism, at the single-node level this usually translates to throughput-oriented task parallelism. This paper focuses on the engineering of two latency-oriented approaches (coarse- and fine-grained) and compares them to the task-parallel approach. We use Powerset’s deployed search engine to evaluate the various factors that affect parallel performance: workload, overhead, load balancing, and resource contention. We also discuss heuristics to selectively control the degree of parallelism and consequent overhead on a query-by-query level. Our experimental results show that using fine-grained parallelism with these dynamic heuristics can significantly reduce query latencies compared to fixed, coarse-granularity parallelization schemes. Although these results were obtained on, and optimized for, Powerset’s semantic search, they can be readily generalized to a wide class of inverted-index search engines.     

A Relation-Based Search Engine in Semantic Web

With the development of the Web, an information "Big Bang" has taken place on the Internet. Search engines have become one of the most helpful tools for obtaining useful information from the Internet. However, instead of caring about the semantics of information, the machine on the current Web cares about the location and display of information only. Because of this shortcoming of the current Web, the search results by even the most popular search engines cannot produce satisfactory results. The development of the next generation Web, semantic Web, will turn the situation around completely. This paper proposes a prototype relation-based search engine, "OntoLook," which has been implemented in a virtual semantic Web environment in our lab. We also present its system architecture and analyze the key algorithm     

基于深度语义信息的查询扩展

随着互联网时代的到来,搜索引擎开始被普遍使用。在针对冷门数据时,由于用户的搜索词范围过小,搜索引擎无法检索出需要的数据,此时查询扩展系统可以有效辅助搜索引擎来提供可靠服务。基于全局文档分析的查询扩展方法,提出结合神经网络模型与包含语义信息的语料的语义相关模型,来更深层地提取词语间的语义信息。这些深层语义信息可以为查询扩展系统提供更加全面有效的特征支持,从而分析词语间的可扩展关系。在近义词林、语言知识库“HowNet”义原标注信息等语义数据中抽取局部可扩展词分布,利用神经网络模型的深度挖掘能力将语料空间中每一个词语的局部可扩展词分布拟合成全局可扩展词分布。在与分别基于语言模型和近义词林的查询扩展方法对比实验中,使用基于语义相关模型的查询扩展方法拥有较高的查询扩展效率;尤其针对冷门搜索数据时,语义相关模型的查全率比对比方法分别提高了11.1个百分点与5.29个百分点。     

基于深度语义信息的查询扩展

随着互联网时代的到来，搜索引擎开始被普遍使用。在针对冷门数据时，由于用户的搜索词范围过小，搜索引擎无法检索出需要的数据，此时查询扩展系统可以有效辅助搜索引擎来提供可靠服务。基于全局文档分析的查询扩展方法，提出结合神经网络模型与包含语义信息的语料的语义相关模型，来更深层地提取词语间的语义信息。这些深层语义信息可以为查询扩展系统提供更加全面有效的特征支持，从而分析词语间的可扩展关系。在近义词林、语言知识库“HowNet”义原标注信息等语义数据中抽取局部可扩展词分布，利用神经网络模型的深度挖掘能力将语料空间中每一个词语的局部可扩展词分布拟合成全局可扩展词分布。在与分别基于语言模型和近义词林的查询扩展方法对比实验中，使用基于语义相关模型的查询扩展方法拥有较高的查询扩展效率；尤其针对冷门搜索数据时，语义相关模型的查全率比对比方法分别提高了11.1个百分点与5.29个百分点。     

The effects of computer-assisted instruction on the achievement,attitudes and retention of fourth grade mathematics students in North Cyprus

The purpose of this study was to examine the effects of the educational software Frizbi Mathematics 4 on 4th grade student's mathematics achievement, retention, attitudes toward mathematics and attitude toward computer assisted learning. Two groups (experimental and control) of students from the state primary school in Gazimagusa, North Cyprus were used in this study. The control group was taught using a lecture-based traditional instruction and experimental group was taught using educational software, namely Frizbi Mathematics 4. The control group consisted of 26 students while the experimental group consisted of 29 students. The groups were compared on achievement of mathematics, retention, and attitude toward mathematics and computer assisted learning. The study included three units, Multiplication of Natural Numbers, Division of Natural Numbers, and Fractions. Scores on achievement tests were collected three times; at the beginning of the study, immediately after the intervention, and 4 months later. The mathematics attitude scale and computer assisted learning attitude scale were administrated only two times; at the beginning of the study and immediately after the completion of the study. A series of ANOVAs for repeated measures revealed significant difference between the groups on the post achievement tests and attitude scales in favor of experimental group. However, statistically significant differences in favor of the treatment group, on the retention tests were attained on the multiplication and division units but not on fractions. The evidence indicates that Frizbi Mathematics 4 for learning and teaching mathematics at the primary school level in North Cyprus is an effective tool.     

The “Panopticon” of search engines: the response of the European data protection framework

Nowadays, Internet users are depending on various search engines in order to be able to find requested information on the Web. Although most users feel that they are and remain anonymous when they place their search queries, reality proves otherwise. The increasing importance of search engines for the location of the desired information on the Internet usually leads to considerable inroads into the privacy of users. A heated debate is currently ongoing at European level regarding the question if search engine providers that are established outside the European Union are covered by the European data protection framework and the obligations it imposes on entities that process personal data. The scope of this paper is to examine the applicability of the European data protection legislation to non-EU-based search engine providers and to study the main privacy issues with regard to search engines, such as the character of search logs, their anonymisation and their retention period. Ixquick, a privacy-friendly meta-search engine, will be presented as an alternative to privacy intrusive existing practices of search engines.     

Retracted: An Empirical Study of an Internet Marketing Strategy for Search Engine Optimization

Over the past few years, more and more Internet visitors are reaching websites through search engines rather than through direct links from another web page. Search engines have come to occupy a prominent position in the online world and are being used to find all kinds of information including things, events, people, and places. The search engine is also coming to play a greater role as a critical link between firms that use the Internet to build their image and find their target customers. How to achieve a high ranking in such search results given certain search words or phrases has become an issue of much interest in Internet marketing. The purpose of the current study is to develop a search engine optimization (SEO) mechanism that can be used by an enterprise to improve the ranking of its website in the search engine results. Social networking sites are included in our exploration of Internet marketing strategy. The proposed mechanism is then applied in the operations of an online ebook store. The website rankings obtained from two well‐known online search engines (Google and Yahoo) are evaluated in efforts to explore a better strategy to ensure higher rankings. The results reveal that a well‐designed SEO strategy, with the incorporation of social networking, can effectively enhance the website's visibility and exposure. Such a strategy will eventually contribute to overall site traffic and improve interaction with customers. © 2012 Wiley Periodicals, Inc.     

智能型元搜索引擎的设计与实现

研究现有元搜索引擎技术，提出了智能型元搜索引擎模型，即采用数据挖掘技术，根据独立型搜索引擎工作情况的记录，动态生成元搜索引擎的调度策略。在对各数据挖掘方法进行比较之后，选择了决策树归纳分类分析技术生成元搜索引擎调用策略，并详细介绍了调度策略的处理过程、系统评估度量的建立以及用微软最近发布的OLE DB for DM数据挖掘通用接口进行数据挖掘的具体实现。     

元搜索引擎在油田领域信息分布式搜索的应用

当前大型集中式企业搜索引擎面临规模扩展、数据更新快速和用户需求专业化、多样化等一系列挑战。因此,在整个油田内建立一个高效、高质量的分布式搜索引擎体系架构,并保证不破坏各公司原有企业搜索引擎的基础之上,实现数据共享变得越来越重要。通过分析油田内部公司搜索引擎现状,结合元搜索引擎技术,提出构建一个合理的油田内部分布式搜索引擎体系架构的解决方案。主要从接口规范,查询调度,排序策略三个方面入手,解决分布式搜索引擎在油田应用查询中存在的问题。     

搜索引擎优化的作弊与防范

随着信息技术的飞速发展,人们越来越多的通过搜索引擎获取信息。快速增长的互联网信息在提供丰富的资源的同时也催生了大量的搜索引擎作弊的行为。本文先是通过对搜索引擎优化的作弊手段进行分析进而提出防范作弊的几种方法。     

国内中文搜索引擎研究

对因特网上较著名的搜索引擎站点进行了详尽分析,着重分析了中文搜索引擎的特点,以及搜索引擎的主要评价标准。最后介绍了国内主要搜索引擎,为人们从因特网上更好地检索信息提供初步指南。     

Comparing Internet search engines

Search engines are sophisticated utilities designed expressly to find information on the global Internet. An expensive combination of high-speed computer networks and specialized software, they are usually created by large corporations and occasionally by universities. They are freely available to anyone with Internet access, and there are no search restrictions. With more than 150 search engines available, choosing the right one (or ones) is important. As with most products, no single engine is best for all searches and all users all the time. After comparing 50 of the most popular and powerful engines, I narrowed the field down to the four I found most useful: Alta Vista, Deja News, Excite and Yahoo     

基于知网与搜索引擎的词汇语义相似度计算

提出一种基于知网与搜索引擎的词汇语义相似度计算方法。利用义原在层次体系树的深度、密度、信息量优化义原的相似性计算。将逐点共有信息（PMI）算法与归一化谷歌距离（NGD）算法结合优化基于搜索引擎的词汇语义相似度计算。将词汇的词性作为权重因子融合知网与搜索引擎的词汇相似度计算结果。实验结果表明,与基于知网和基于搜索引擎的语义相似度计算方法相比,所提出的方法在NLPCC测试集上的平均相似度更接近于测试集的评测标准,在汽车票务领域的词汇相似度计算中具有较好的应用效果。     

SEO技术研究与应用

SEO是英文Search Engine Optimization的缩写,其中文意思是搜索引擎优化。SEO是搜索引擎的产物,确切地说是互联网的必然产物,是借助搜索引擎这个媒体顺势而生。SEO为了提升互联网质量,方便检索而存在。搜索引擎的快速发展,从简单到复杂,从单一到全面,逐步完善自己的王国。页面优化,外链导入的作用逐步减小,而涉及到网站关键词的分析,高质量内容的建设,网站的诚信度,用户的体验以及融合到社会中的社会化搜索等逐步增加。SEO就是提升网站的质量。     

基于搜索引擎的信息查询技术研究

随着网络的快速发展,搜索引擎日益成为处理信息的主流工具。Internet是世界上资料最多、规模最大的信息资料库。在WWW上进行信息查找有三种方法,即基于超文本的信息查询、基于目录的信息查询、基于搜索引擎的信息查询,网络信息检索核心工具是搜索引擎。本文从搜索引擎概述、查询技术方法及展望三方面进行阐述。