面向信息检索的藏文文本索引策略研究

互联网文本数量持续爆炸式增长,用户通过互联网查找信息变得更加困难,响应时间得不到满足。针对藏文本身的语言学特点,探讨一种面向信息搜索的藏文文本索引建立策略,建立一种高效的藏文文本索引,以提高藏文信息检索速度。     

User-centered indexing for adaptive information access

We are focusing on information access tasks characterized by large volume of hypermedia connected technical documents, a need for rapid and effective access to familiar information, and long-term interaction with evolving information. The problem for technical users is to build and maintain a personalized task-oriented model of the information to quickly access relevant information. We propose a solution which provides user-centered adaptive information retrieval and navigation. This solution supports users in customizing information access over time. It is complementary to information discovery methods which provide access to new information, since it lets users customize future access to previously found information. It relies on a technique, called Adaptive Relevance Network, which creates and maintains a complex indexing structure to represent personal user's information access maps organized by concepts. This technique is integrated within the Adaptive HyperMan system, which helps NASA Space Shuttle flight controllers organize and access large amount of information. It allows users to select and mark any part of a document as interesting, and to index that part with user-defined concepts. Users can then do subsequent retrieval of marked portions of documents. This functionality allows users to define and access personal collections of information, which are dynamically computed. The system also supports collaborative review by letting users share group access maps. The adaptive relevance network provides long-term adaptation based both on usage and on explicit user input. The indexing structure is dynamic and evolves over time. Learning and generalization support flexible retrieval of information under similar concepts. The network is geared towards more recent information access, and automatically manages its size in order to maintain rapid access when scaling up to large hypermedia space. We present results of simulated learning experiments.Dr. Mathé and Dr. Chen are contractors with Recom Technologies, Inc.     

SEEKER:基于关键词的关系数据库信息检索

传统上,SQL是存取关系数据库中数据的主要界面.但是,对于没有经验的用户来说,学习复杂的SQL语法是一件困难的事情.实现基于关键词的关系数据库信息检索,将使用户不需要任何SQL语言和底层数据库模式的知识,用搜索引擎的方式来获取数据库中的相关数据.描述了一个基于关键词的关系数据库信息检索系统SEEKER的设计和实现.现有的关系数据库关键词查询系统只能检索关系数据库中的文本属性,而SEEKER还可以检索数据库元数据以及数字属性.并且,SEEKER采用了更合理的排序公式,支持Top-k查询.实验结果显示,SEEKER具有良好的查询性能.     

Using KCCA for Japanese–English cross-language information retrieval and document classification

Kernel Canonical Correlation Analysis (KCCA) is a method of correlating linear relationship between two variables in a kernel defined feature space. A machine learning algorithm based on KCCA is studied for cross-language information retrieval. We apply the algorithm in Japanese–English cross-language information retrieval. The results are quite encouraging and are significantly better than those obtained by other state of the art methods. Computational complexity is an important issue when applying KCCA to large dataset as in information retrieval. We experimentally evaluate several methods to alleviate the problem of applying KCCA to large datasets. We also investigate cross-language document classification using KCCA as well as other methods. Our results show that it is feasible to use a classifier learned in one language to classify the documents in other languages.     

搜索引擎综合分析

随着互联网的广泛应用,搜索引擎成为了越来越多的用户从海量信息中获取知识必不可少的工具.说明了搜索引擎当前发展的现状,简述了搜索引擎的分类,基本原理和工作机制,重点分析了搜索引擎的检索技术及页面排序方法,最后介绍了搜索引擎面临的挑战和未来发展趋势.     

基于网络用户行为的搜索引擎系统SISI

提出了一种基于网络用户行为的搜索引擎SISl(Similar Interest,Similar access on Internet)。SISI的查询输入是一个Web文档的URL。SISI的检索模型是使用统计的方法基于网络日志中用户对文档的访问频率挖掘相关文档,充分利用了用户在相关文档判定上的潜在意识。模型的假设基础是一组兴趣相似的人访问的文档有可能相关。与传统的搜索引擎相比较,搜索引擎SISI具有系统初始化时间代价小、空间代价小等优点。同时SISI的检索优势在于可以查找那些没有显式相似内容的相关文档,尤其是在检索处理时避开了文档的类型,将文本文档和多媒体文档一视同仁。     

网络信息的检索与挖掘回顾

随着互联网的蓬勃发展,海量的网络信息成为了迄今为止最大规模的数据资源。如何利用海量网络信息,为人们提供智能应用,更好的解决人们的信息需求,成为了互联网领域的挑战性问题,也催生了对海量网络信息检索与挖掘的广泛研究。该文从信息表达、信息检索与信息挖掘三个方向入手,结合近年来对网络信息相关领域的研究与实践,对网络信息检索与挖掘的发展变化历程、目前存在的问题以及未来的发展趋势进行总结和分析。     

Distributed and cooperative information retrieval on the World Wide Web

A masss of heterogeneous,distributed and dynamic information on the World Wide Web(the Web) has resulted in “information overload“ .It‘s an important and urgent reserach issue to provide users with effective information retrieval service on the Web.Web search enginees attempt to solve this problem,yet their effect is far from satisfying.In this paper,a distributed and cooperative strategy for information retrieval on the Web is proposed to substitute the centralized mode adopted by the current search engines.Then a new information retrieval system model IRSM is presented.which supports the retrieval of metadata about web documents and uses Z39.50 standard protocol to unify the heterogeneous interfaces of uments and uses Z39.50 standard protocol to unify the heterogeneous interfaces of different systems.Based on that,a distributed and cooperative information refieval framework,called DCIRF,is designed to help users in fast and effective information retrieval on the Web.     

面向在线空间信息的自动化搜索

近年来,越来越多的空间信息实现了在线发布和在线更新。但这些在线空间信息的分布广泛性和发展无序性导致了最终用户难以找到所需的在线空间信息,因此面向在线空间信息的自动化搜索已经成为空间信息共享的一个重要研究内容,其设计目标为自动地帮助用户寻找感兴趣的空间信息。论文从互联网上空间信息的存在形式和提供方式入手,分析了网络空间信息系统的一般结构;通过从搜索对象、搜索方法和用户界面等方面对通用Web信息搜索和面向空间信息搜索进行了比较,得出了实现在线空间信息的自动化搜索必须首先规范化网络空间信息系统的结论,最后总结了面向空间信息的搜索需要解决的困难并分析指出其研究的主要内容。     

信息检索常用技术与技巧

信息检索技术能帮助人们快捷、准确、全面地获取所需知识,最大限度地节省查找时间,使信息检索过程变得事半功倍,使信息能够得到充分利用。本文针对信息检索提出几种常用的技术和技巧,以为用户进行信息检索提供一些借鉴。     

A Method for Supporting Document Selection in Cross-language Information Retrieval and its Evaluation

It is important to give useful clues for selecting desiredcontent from a number of retrieval results obtained (usually) from avague search request. Compared with monolingual retrieval, such asupport framework is inevitable and much more significant for filteringgiven translingual retrieval results. This paper describes an attempt toprovide appropriate translation of major keywords in each document in across-language information retrieval (CLIR) result, as a browsingsupport for users. Our idea of determining appropriate translation ofmajor keywords is based on word co-occurrence distribution in thetranslation target language, considering the actual situation of WWWcontent where it is difficult to obtain aligned parallel (multilingual)corpora. The proposed method provides higher quality of keywordtranslation to yield a more effective support in identifying the targetdocuments in the retrieval result. We report the advantage of thisbrowsing support technique through evaluation experiments includingcomparison with conditions of referring to a translated documentsummary, and discuss related issues to be examined towards moreeffective cross-language information extraction.     

Smartphone Information Displays When Reading News in Persian and English Languages

By their nature, smartphones must have small screens, and that is one of their limitations. Many users have trouble reading information on the Internet on such small screens because Internet browsers are usually designed for computers that have larger screens than smartphones. This study evaluates the usability of alternative user interfaces when reading news articles on smartphones. An experiment was conducted involving 120 smartphone users who were asked to evaluate six types of user interfaces based on three methods (pop-up, full-screen, and auto-zooming) and two display orientations (horizontal, vertical) in one of two languages (English and Persian). The participants were assigned four typical tasks that users must perform to obtain information from the Internet, that is, finding, refinding, reading, and browsing; they were asked to conduct the tasks in random order. In addition, a questionnaire was used to measure the efficiency and effectiveness of the participants’ completion of the tasks, as well as their satisfaction, compatibility, and enjoyment of the undertakings. The results indicated that method, orientation, and language affected the actual usage and the time used. Based on the human factor experiment, the full-screen method was preferred in refinding and reading, whereas the pop-up method was preferred in browsing and finding. In terms of orientation, the vertical mode was preferred, and each user’s performance in the vertical mode was better in all tasks except browsing. Of interest, using the English language turned out to be more satisfying, enjoyable, and efficient to the Persian users who did the experiment in English as their second language.     

一种基于位平面综合特征的彩色图像检索方案

传统的基于颜色直方图的彩色图像检索方法存在严重不足.首先是丢失颜色空间分布信息及特征维数过高,更重要的是无法有效检索含噪声图像.为克服此缺陷,提出了一种基于位平面综合特征的彩色图像检索算法.首先,结合光照、锐化、模糊等噪声攻击特点,从原始彩色图像中提取出重要位平面;然后选取重要位平面的加权颜色直方图作为颜色特征,选取重要位平面的空间信息熵作为空间特征;再综合利用上述颜色、空间两个特征计算图像间内容的相似度,并进行彩色图像检索.仿真实验表明,算法能够准确和高效地查找出用户所需内容的彩色图像,并且具有较好的查准率和查全率(特别对于含噪声图像).     

A Knowledge-Based Approach to Effective Document Retrieval

This paper presents a knowledge-based approach to effective document retrieval. This approach is based on a dual document model that consists of a document type hierarchy and a folder organization. A predicate-based document query language is proposed to enable users to precisely and accurately specify the search criteria and their knowledge about the documents to be retrieved. A guided search tool is developed as an intelligent natural language oriented user interface to assist users formulating queries. Supported by an intelligent question generator, an inference engine, a question base, and a predicate-based query composer, the guided search collects the most important information known to the user to retrieve the documents that satisfy users' particular interests. A knowledge-based query processing and search engine is devised as the core component in this approach. Algorithms are developed for the search engine to effectively and efficiently retrieve the documents that match the query.     

网络搜索引擎的性能优化策略和相关技术

由于检索结果的不准确性,使网络搜索引擎有时难以满足用户的查询需求。因此,在传统搜索引擎技术的基础上,采用其它理论和技术来提高搜索引擎的查准率,可以对搜索引擎进行性能优化。该文提出了几种对网络搜索引擎进行性能优化的策略,并对相关的实现技术进行了探讨。根据网络资源的权威性及其与用户查询的相关性对检索结果进行排序,可以有效提高结果的准确度;通过基于概念的信息检索技术和信息的自动分类技术可以有效地对用户查询进行语义的扩充和理解,更好地满足用户需求;实现搜索引擎的个性化查询和专业化查询,也是提高搜索引擎性能的重要途径。     

A conceptual model for user-centered quality information retrieval on the World Wide Web

Information retrieval from the Internet is becoming a commonplace phenomenon. Users and consumers are browsing websites and seeking various kinds of information for personal use. Retrieving quality information from the Internet can be challenging even for the computer-savvy. There are several search engines, even some personalized, to help users search for information on the Internet. In spite of all the claims about search engines, users still have difficult time retrieving relevant information quickly. This paper proposes a general conceptual model for user-centered quality information retrieval (UCQIR) from the Internet. The UCQIR conceptual model is presented in an architectural form. The UCQIR architectural model uses the concept of “Task-performer” to present various aspects of an information retrieval system at the knowledge level. Task-performer is an abstract construct used to conceptualize the idea of an entity that is competent in doing its tasks. The UCQIR architectural model can be used to easily design and develop domain-specific, user-centered quality information retrieval systems. The proposed UCQIR conceptual model is unique and comprehensive. The use of the conceptual model is illustrated through a design of a patient-centered quality medical information retrieval for the medical domain. We also present an experimental evaluation of a UCQIR prototype based upon real user experiences. The experimental results are very positive.     

基于元数据与Z39.50的分布协作式Web信息检索

Web上大量的异质、分布、动态的信息造成了“信息过载”.如何有效地为用户提供Web信息检索已经成为一项重要的研究课题.Web搜索引擎部分地解决了信息检索问题,然而其效果却远远不能令人满意.提出了Web信息检索的分布协作策略以取代传统的集中式信息检索方式;给出了一种新的Web信息检索系统模型,该模型支持对Web文档的元数据进行检索,并采用Z39.50协议作为接口标准,以克服不同信息检索系统之间的访问异构性.在此基础上,设计了一个分布协作式Web信息检索框架,用以帮助用户有效地进行Web信息检索.     

Information Filtering: Overview of Issues,Research and Systems

An abundant amount of information is created and delivered over electronic media. Users risk becoming overwhelmed by the flow of information, and they lack adequate tools to help them manage the situation. Information filtering (IF) is one of the methods that is rapidly evolving to manage large information flows. The aim of IF is to expose users to only information that is relevant to them. Many IF systems have been developed in recent years for various application domains. Some examples of filtering applications are: filters for search results on the internet that are employed in the Internet software, personal e-mail filters based on personal profiles, listservers or newsgroups filters for groups or individuals, browser filters that block non-valuable information, filters designed to give children access them only to suitable pages, filters for e-commerce applications that address products and promotions to potential customers only, and many more. The different systems use various methods, concepts, and techniques from diverse research areas like: Information Retrieval, Artificial Intelligence, or Behavioral Science. Various systems cover different scope, have divergent functionality, and various platforms. There are many systems of widely varying philosophies, but all share the goal of automatically directing the most valuable information to users in accordance with their User Model, and of helping them use their limited reading time most optimally. This paper clarifies the difference between IF systems and related systems, such as information retrieval (IR) systems, or Extraction systems. The paper defines a framework to classify IF systems according to several parameters, and illustrates the approach with commercial and academic systems. The paper describes the underlying concepts of IF systems and the techniques that are used to implement them. It discusses methods and measurements that are used for evaluation of IF systems and limitations of the current systems. In the conclusion we present research issues in the Information Filtering research arena, such as user modeling, evaluation standardization and integration with digital libraries and Web repositories.     

基于本体的跨语言信息检索模型

随着网络信息的日益丰富和用户需求的提高,人们已经不能满足于仅仅在同一语种中进行检索,跨语言的信息检索(CLIR)因而受到人们越来越多的关注。为此,本文提出了一种新的基于语义的跨语言信息检索模型Onto-CLIR,该模型在传统信息检索技术的基础上,利用本体来刻画不同语言中对应的领域知识,以解决从查询语言到检索语言之间转换过程中出现的语义损失和曲解等问题,从而保证在检索过程中能够有效地遵循用户的查询意图,获得预期的检索信息。本文以体育新闻检索为背景,以英文查询作为查询请求,检索来自新浪网的体育类新闻,结果表明采用基于本体的跨语言信息检索方法之后检索的查全率和查准率平均提高10个百分点左右,有效地改善了检索性能。