User perceptions and expectations of an information retrieval system

Abstract

Performance measures are frequently used to evaluate user friendliness of a system. An equally important, but often overlooked factor is the users' attitudes towards a system. A prototype interface for information retrieval was developed for presenting engineering manuals online. It was tested on a representative sample of the intended end user community. We found that subjects' expectations were based on their experience with printed materials and other computer systems. Familiar search mechanisms (e.g., table of contents, index) were important for getting them started, even though they switched to other mechanisms as they gained more experience with the system. The fact that the index was more detailed than the one in the printed manual was seen by the subjects as critical for speedy and efficient information retrieval. Keyword search of the database was generally the preferred retrieval mechanism. However, some users preferred the index. The ‘Table of Contents’ which was a tree structured menu based system was found to be of limited use in the electronic medium, in contrast to the printed manual.     

RésuMatcher: A personalized résumé-job matching system

Online jobs search through popular websites are quite beneficial having served for many years as a prominent tool for job seekers and employers alike. In spite of their valuable utility in linking employers with potential employees, the search process and technology utilized by job search websites have not kept pace with the rapid changes in computing capability and machine intelligence. The Information retrieval techniques utilized by these websites rely primarily on variants of manually entered search queries with some advanced similarity metrics for ranking search results.Advancements in machine intelligence techniques have enabled programmatic extraction of pertinent information about the job seeker and job postings without active user input. To this end, we developed a resume matching system, RésuMatcher, which intelligently extracts the qualifications and experience of a job seeker directly from his/her résumé, and relevant information about the qualifications and experience requirements of job postings. Using a novel statistical similarity index, RésuMatcher returns results that are more relevant to the job seekers experience, academic, and technical qualifications, with minimal active user input.Our method provides up to a 34% improvement over existing information retrieval methods in the quality of search results. In addition however, RésuMatcher requires minimal active user input to search for jobs, compared to traditional manual search-based methods prevalent today. These improvements, we hypothesize, will lead to more relevant job search results and a better overall job search experience for job seekers.As an alternative to the fragmented organization-centric job application process, job recruitment websites offered the promise of simplifying and streamlining the job search process. However, these websites offer limited functionality using generic and simplistic information retrieval methods, which being non-domain lead to a poor and frustrating search experience. In this paper, we present RésuMatcher, a personalized job-résumé matching system, which offers a novel statistical similarity index for ranking relevance between candidate résumés and a database of available jobs. In our experiments we show that our method offers a 37.44% improvement over existing information retrieval methods in the quality of matches returned.     

Improving visual search in instruction manuals using pictograms*

Instruction manuals provide important messages about the proper use of a product. They should communicate in such a way that they facilitate users’ searches for specific information. Despite the increasing research interest in visual search, there is a lack of empirical knowledge concerning the role of pictograms in search performance during the browsing of a manual’s pages. This study investigates how the inclusion of pictograms improves the search for the target information. Furthermore, it examines whether this search process is influenced by the visual similarity between the pictograms and the searched for information. On the basis of eye-tracking measurements, as objective indicators of the participants’ visual attention, it was found that pictograms can be a useful element of search strategy. Another interesting finding was that boldface highlighting is a more effective method for improving user experience in information seeking, rather than the similarity between the pictorial and adjacent textual information. Implications for designing effective user manuals are discussed.

Practitioner Summary: Users often view instruction manuals with the aim of finding specific information. We used eye-tracking technology to examine different manual pages in order to improve the user’s visual search for target information. The results indicate that the use of pictograms and bold highlighting of relevant information facilitate the search process.     

On the role of trust in collaborative Web search

Recommender systems combine ideas from information retrieval, user modelling, and artificial intelligence to focus on the provision of more intelligent and proactive information services. As such, recommender systems play an important role when it comes to assisting the user during both routine and specialised information retrieval tasks. Like any good assistant it is important that users can trust in the ability of a recommender system to respond with timely and relevant suggestions. In this paper, we will look at a collaborative recommendation system operating in the domain of Web search. We will show how explicit models of trust can help to inform more reliable recommendations that translate into more relevant search results. Moreover, we demonstrate how the availability of this trust-model facilitates important interface enhancements that provide a means to declare the provenance of result recommendations in a way that will allow searchers to evaluate their likely relevance based on the reputation and trustworthiness of the recommendation partners behind these suggestions.     

基于用户兴趣的个性化搜索引擎的设计

建立了个性化条件下的用户兴趣模型。该模型借助于对用户自身信息和其他用户访问信息的挖掘,得到用户兴趣向量,并以此对检索结果进行过滤,从而使用户得到的检索结果能够满足用户个人爱好。最后,本文应用该模型设计了一个个性化搜索引擎系统。     

基于模糊语言方法的信息检索系统的研究

该文提出了一个基于模糊语言方法的信息检索系统模型。该系统分为查询界面子系统、数据库子系统和检索子系统三大部分。在查询界面子系统,用布尔表达式表示用户的查询请求,并对每个查询关键词赋予了两种不同语义的语言值权重,该权重表达了用户的模糊检索要求;在数据库子系统,用索引词一文档模糊矩阵表示待检索的文档,对每个索引词。根据其在文档中的出现频率大小。引入了数值权重;在检索子系统,运用模糊语言方法,对用户输入的布尔查询表达式与索引词一文档模糊矩阵进行自底向上的模糊匹配,最后返回满足用户要求的检索结果。相对于传统的基于查询关键词精确匹配的检索系统而言,该系统能较好地满足用户查询要求中的灵活性。     

Towards a multimedia World-Wide Web information retrieval engine

Search engines are useful because they allow the user to find information of interest from the World-Wide Web. However, most of the popular search engines today are textual; they do not allow the user to find images from the Web. This paper describes a search engine that integrates text and image search. One or more Web sites can be indexed for both textual and image information, allowing the user to search based on keywords or images or both. Another problem with the current search engines is that they show the results as pages of scrolled list; this is not very user-friendly. Therefore our search engine allows the user to visualize the results in various ways. This paper explains the indexing and searching techniques of the search engine and highlights several features of the querying interface to make the retrieval process more efficient. Examples are used to show the usefulness of the technology.     

Information retrieval from the World Wide Web: a user-focused approach based on individual experience with search engines

Although search engines are essential tools for finding information on the World Wide Web, the effective use of search engines for information retrieval (IR) is a crucial challenge for any Internet user. Based on the user-focused approach, this study investigates individual information retrieval behaviors using information processing theory. The results show that experience with search engines significantly affects users’ attitudes toward search engines for information retrieval, the query-based service is more popular than the directory-based service, users are not completely satisfied with the precision of retrieved information and the response time of search engines, and users’ motivation is a key factor that predicts their intention to use search engines for information retrieval. Furthermore, this study proposes a conceptual model for investigating individual attitudes toward search engines for information retrieval.     

个性化搜索引擎中用户模型智能调整算法的研究

个性化信息服务越来越成为信息检索领域中研究的热点。针对用户模型构造问题,文章结合手工定制建模与自动分析建模技术,利用空间向量模型表示法,提出了一种用户模型智能调整算法。模拟实验表明,该结构和算法能够有效地提高检索结果的准确度,并且具有良好的可适应性。     

Fuzzy User Modeling for Information Retrieval on the World Wide Web

Information retrieval from the World Wide Web through the use of search engines is known to be unable to capture effectively the information needs of users. The approach taken in this paper is to add intelligence to information retrieval from the World Wide Web, by the modeling of users to improve the interaction between the user and information retrieval systems. In other words, to improve the performance of the user in retrieving information from the information source. To effect such an improvement, it is necessary that any retrieval system should somehow make inferences concerning the information the user might want. The system then can aid the user, for instance by giving suggestions or by adapting any query based on predictions furnished by the model. So, by a combination of user modeling and fuzzy logic a prototype system has been developed (the Fuzzy Modeling Query Assistant (FMQA)) which modifies a user's query based on a fuzzy user model. The FMQA was tested via a user study which clearly indicated that, for the limited domain chosen, the modified queries are better than those that are left unmodified. Received 10 November 1998 / Revised 14 June 2000 / Accepted in revised form 25 September 2000     

基于智能Agent的Web信息检索系统

设计和实现了一个基于智能Agent的面向领域的Web信息检索系统，讨论了该系统的体系结构和各模块设计思想。经实验验证，该系统具有检索精度商、检索方式多样、用户界面友好等特点。     

基于内容的中文文本检索方法

随着信息量的急剧增加,检索技术显得尤为关键.目前很多检索技术都是基于索引的检索技术.文中借助了Lucene的索引技术与检索机制,通过对索引信息的改进以及使用基于内容的改进方法,对Lucene结果与查询语句在向量空间中重新计算相似度,实现了对长段查询语句检索结果排序位置的提高.     

A hybrid system for German encyclopedia alignment

Collaboratively created on-line encyclopedias have become increasingly popular. Especially in terms of completeness they have begun to surpass their printed counterparts. Two German publishers of traditional encyclopedias have reacted to this challenge and started an initiative to merge their corpora to create a single, more complete encyclopedia. The crucial step in this merging process is the alignment of articles. We have developed a two-step hybrid system to provide high-accurate alignments with low manual effort. First, we apply an information retrieval based, automatic alignment algorithm. Second, the articles with a low confidence score are revised using a manual alignment scheme carefully designed for quality assurance. Our evaluation shows that a combination of weighting and ranking techniques utilizing different facets of the encyclopedia articles allow to effectively reduce the number of necessary manual alignments. Further, the setup of the manual alignment turned out to be robust against inter-indexer inconsistencies. As a result, the developed system empowered us to align four encyclopedias with high accuracy and low effort.     

Intranet搜索引擎设计与实现

随着企业内部网络应用的深入,Intranet内部的信息资源越来越庞大,怎样为这些数据信息构建索引是我们面If缶的主要任务,而全文检索的产生解决了这一问题。目前越来越多的中小企业采用Linux系统作为Web平台,并且利用检索系统来管理内部繁多的文本和HTML文件。文章对www搜索引擎的全文检索及其相关技术进行了分析和讨论,实现了一个基于Linux环境的Intranet搜索引擎LISE（Linux Intranet Search Engine）。LISE利用了基于词表的索引方法,为用户提供了更加准确的信息,能满足多种中小企业用户的需求。     

基于日志挖掘的搜索引擎用户行为分析

随着网络搜索用户的大规模增加,网络用户行为分析已成为网络信息检索系统进行架构分析、性能优化和系统维护的重要基石,是网络信息检索和知识挖掘的重要研究领域之一。为更好理解网络用户的搜索行为,该文基于7.56亿条真实网络用户行为日志,对用户行为进行分析和研究。我们主要考察了用户搜索行为中的查询长度、查询修改率、相关搜索点击率、首次/最后一次点击位置分布以及查询内点击数分布等信息。该文还基于不同类型的查询集合,考察用户在不同查询需求下的行为差异性。相关分析结果对搜索引擎算法优化和系统改进等都具有一定的参考意义。     

基于UDDI Registry的智能检索引擎的研究

随着Web Services技术的不断成熟和发展,存储在UDDI Registry中的Web Service信息将会变得越来越庞大,如何从UDDI Registry浩如烟海的信息资源中为用户快速、方便、准确地检索出满足需求的Web Service,将变得十分重要.而传统的基于关键词匹配的检索技术已不能满足用户准确而全面定位信息的要求.因此,以Web Service的文本描述信息为研究对象,运用文本挖掘相关方法,构建出用户概念空间,对用户提出的查询要求进行概念检索.着重介绍了用户概念空间的构建方法以及概念检索的匹配运算过程,并给出了应用于UDDI Registry的一种智能检索引擎系统模型.     

Personalized mining of web documents using link structures and fuzzy concept networks

Personalized search engines are important tools for finding web documents for specific users, because they are able to provide the location of information on the WWW as accurately as possible, using efficient methods of data mining and knowledge discovery. The types and features of traditional search engines are various, including support for different functionality and ranking methods. New search engines that use link structures have produced improved search results which can overcome the limitations of conventional text-based search engines. Going a step further, this paper presents a system that provides users with personalized results derived from a search engine that uses link structures. The fuzzy document retrieval system (constructed from a fuzzy concept network based on the user's profile) personalizes the results yielded from link-based search engines with the preferences of the specific user. A preliminary experiment with six subjects indicates that the developed system is capable of searching not only relevant but also personalized web pages, depending on the preferences of the user.     

交叉语言信息检索研究进展

Web上多种语言描述的信息形成“信息过载”,如何在传统的单语言信息检索技术的基础上开展对交叉语言信息检索的研究已经成为一项重要的研究课题。交叉语言信息检索的特殊性,给用户理解带来不少的困惑,同时缺乏完整的技术分析。该文全面分析了信息检索系统的原理和交叉语言信息检索系统的特殊技术。