Information retrieval and hypertext: competing technologies or complementary access methods

Abstract. Information retrieval typically involves accessing textual information from a database in response to a user's vague information need. Hypertext or hypermedia, on the other hand, involves a user browsing through a database of textual or multimedia information in response to a variety of types of information need. Thus information retrieval can be said to have a searching metaphor while hypertext has a browsing analogy. Initially, these two technologies for information access appear to be very different, almost competitive in nature. In this paper information retrieval systems are briefly reviewed and hypertext systems are also examined. These two techniques for accessing information have been integrated into a prototype system which is described. The system dynamically generates guided tours in response to a user's query and the tour guides the user through the hypertext. Some experiments reporting on the effectiveness of this as an information access strategy are given.     

Designing for Semantic Access: A Video Browsing System

Users of browsing applications often have vague information needs which can only be described in conceptual terms. Therefore, a video browsing system must accept conceptual queries for preselection and offer mechanisms for interactive inspection of the result set by the user. In this paper, we describe a MM-DBMS that we extended with the following components: Our retrieval engine calculates relevance values for the results of a conceptual query by feature aggregation on video shot granularity to offer conceptual, content-based access. To reduce startup delays within sessions, our admission control module admits only complete browsing sessions, if required resources, which are heuristically predicted from query results, are available. In addition, our intelligent client buffer strategy employs the retrieval relevance values to enable flexible user interactions during browsing.     

On research issues regarding uncertain query processing in an office document retrieval system

TEXPROS (TEXT PROcessing System) is an intelligent document processing, system; it supports storing, extracting, classifying, categorizing, retrieving, and browsing information from a variety of office documents [76]. This article presents a retrieval subsystem for TEXPROS, which is capable of processing incomplete, imprecise, and vague queries, and providing semantically meaningful responses to the user. The design of the retrieval subsystem is highly integrated with various mechanisms for achieving these goals. First, a system catalog including a thesaurus is used to store the knowledge about the database. Second, there is a query transformation mechanism composed of context construction and algebraic query formulation modules. Given an incomplete or imprecise query, the context construction module searches the system for the required terms and constructs a query that has a complete and precise representation: The resulting query is then formulated into an algebraic expression. Third, in practice, the user may not have a clear idea of what he is searching for. A browing mechanism is employed for such situations to assist the user in the retrieval process. With the browser, vague queries can be entered into the system until sufficient information, is obtained to the extent that the user is able to construct a query for his request. Finally, when processing of queries fails by responding with a null answer to the user, a generalizer mechanism is used to give the user cooperative explanation for the null answer. The presented techniques will contribute to our research toward development of highly intelligent data processing facilities beyond the present scope of database technology.This work was supported, in part, by the New Jersey Institute of Technology under grant No. 421280 and by a grant from the AT&T Foundation.     

A framework for reuse of user experience in Web browsing

This paper examines aspects affecting user behaviours in Web browsing with a discussion of existing models for both the computer and human aspects of Web browsing. Problems in Web information retrieval are analysed and studies related to the reuse of user experience in Web browsing are reviewed. An object-oriented model for user behaviours in Web browsing is proposed in which both the information from the Web and the information retained by users are modelled as objects. Thus, user actions on the Web are described as a graph of objects or transformations from one object to another. A framework for reuse of user experience is provided. The possible methods of reusing Web browsing experience are described for the scenario of reusing by oneself (history mechanism, prediction) or reusing by others (collaborative filtering, instructions).     

A framework for reuse of user experience in Web browsing

This paper examines aspects affecting user behaviours in Web browsing with a discussion of existing models for both the computer and human aspects of Web browsing. Problems in Web information retrieval are analysed and studies related to the reuse of user experience in Web browsing are reviewed. An object-oriented model for user behaviours in Web browsing is proposed in which both the information from the Web and the information retained by users are modelled as objects. Thus, user actions on the Web are described as a graph of objects or transformations from one object to another. A framework for reuse of user experience is provided. The possible methods of reusing Web browsing experience are described for the scenario of reusing by oneself (history mechanism, prediction) or reusing by others (collaborative filtering, instructions).     

MIDS: a framework for information organization and discovery

The MITRE Information Discovery System (MIDS) is a baseline system for integrating advanced processing tools for information discovery and retrieval in large-scale distributed environments. The system is built on a modular, extendible architecture that allows for system-level decoupling and allocation of component processing tools across network nodes to provide for efficient processing in distributed environments. At one level, the system provides for multi-platform user access to HTTP, Gopher, FTP, and news servers using an HTML based client interface. However, more significantly, the system provides advanced tools for metadata generation from disparate network objects, and a content routing mediation layer for classification of metadata into appropriate information brokers. This bottom-up layered information organization approach supports a wide range of information retrieval and browsing strategies.     

Tolerant Information Retrieval with Backpropagation Networks

Neural networks can learn from human decisions and preferences. Especially in human-computer interaction, adaptation to the behaviour and expectations of the user is necessary. In information retrieval, an important area within human-computer interaction, expectations are difficult to meet. The inherently vague nature of information retrieval has led to the application of vague processing techniques. Neural networks seem to have great potential to model the cognitive processes involved more appropriately. Current models based on neural networks and their implications for human-computer interaction are analysed. COSIMIR (Cognitive Similarity Learning in Information Retrieval), an innovative model integrating human knowledge into the core of the retrieval process, is presented. It applies backpropagation to information retrieval, integrating human-centred and soft and tolerant computing into the core of the retrieval process. A further backpropagation model, the transformation network for heterogeneous data sources, is discussed. Empirical evaluations have provided promising results.     

Instance based personalized multi-form image browsing and retrieval

It is important to adapt and personalize image browsing and retrieval systems based on users’ preferences for improved user experience and satisfaction. In this paper, we present a novel instance based personalized multi-form image representation with implicit relevance feedback and adaptive weighting approach for image browsing and retrieval systems. In the proposed system, images are grouped into forms, which represent different information on images such as location, content etc. We conducted user interviews on image browsing, sharing and retrieval systems for understanding image browsing and searching behaviors of users. Based on the insights gained from the user interview study we propose an adaptive weighting method and implicit relevance feedback for multi-form structures that aim to improve the efficiency and accuracy of the system. Statistics of the past actions are considered for modeling the target of the users. Thus, on each iteration weights of the forms are updated adaptively. Moreover, retrieval results are modified according to the users’ preferences on iterations in order to improve personalized user experience. The proposed method has been evaluated and results are illustrated in the paper. It is shown that, satisfactory improvements can be achieved with proposed approaches in the multi-form scheme.     

个性化浏览中网页推荐的结构模型

1 前言随着互联网建设的不断发展,网站和网页数目都已经很难用Lawrence在Science和Nature给出的结论来估算。每个在网上冲浪的人都有体会,迷失在Internet浩瀚的资料中是多么容易。世界上最大的搜索引擎Google已经宣称搜索并索引了2,073,418,204张网页,在这近21亿索引并分类的网页中搜索,用户同样会迷失在层层链接之中。     

InsightVideo: toward hierarchical video content organization for efficient browsing, summarization and retrieval

Hierarchical video browsing and feature-based video retrieval are two standard methods for accessing video content. Very little research, however, has addressed the benefits of integrating these two methods for more effective and efficient video content access. In this paper, we introduce InsightVideo, a video analysis and retrieval system, which joins video content hierarchy, hierarchical browsing and retrieval for efficient video access. We propose several video processing techniques to organize the content hierarchy of the video. We first apply a camera motion classification and key-frame extraction strategy that operates in the compressed domain to extract video features. Then, shot grouping, scene detection and pairwise scene clustering strategies are applied to construct the video content hierarchy. We introduce a video similarity evaluation scheme at different levels (key-frame, shot, group, scene, and video.) By integrating the video content hierarchy and the video similarity evaluation scheme, hierarchical video browsing and retrieval are seamlessly integrated for efficient content access. We construct a progressive video retrieval scheme to refine user queries through the interactions of browsing and retrieval. Experimental results and comparisons of camera motion classification, key-frame extraction, scene detection, and video retrieval are presented to validate the effectiveness and efficiency of the proposed algorithms and the performance of the system.     

Texture features for browsing and retrieval of image data

Image content based retrieval is emerging as an important research area with application to digital libraries and multimedia databases. The focus of this paper is on the image processing aspects and in particular using texture information for browsing and retrieval of large image data. We propose the use of Gabor wavelet features for texture analysis and provide a comprehensive experimental evaluation. Comparisons with other multiresolution texture features using the Brodatz texture database indicate that the Gabor features provide the best pattern retrieval accuracy. An application to browsing large air photos is illustrated     

Browsing functions in three-dimensional space for digital libraries

In order to get useful information from various kinds of information sources, we first apply a searching process with query statements to retrieve candidate data objects (called a hunting process in this paper) and then apply a browsing process to check the properties of each object in detail by visualizing candidates. In traditional information retrieval systems, the hunting process determines the quality of the result, since there are only a few candidates left for the browsing process. In order to retrieve data from widely distributed digital libraries, the browsing process becomes very important, since the properties of data sources are not known in advance. After getting data from various information sources, a user checks the properties of data in detail using the browsing process. The result can be used to improve the hunting process or for selecting more appropriate visualization parameters. Visualization relationships among data are very important, but will become too time-consuming if the amount of data in the candidate set is large, for example, over one hundred objects. One of the important problems in handling information retrieval from a digital library is to create efficient and powerful visualization mechanisms for the browsing process. One promising way to solve the visualization problem is to map each candidate data object into a location in three-dimensional (3D) space using a proper distance definition. In this paper, we will introduce the functions and organization of a system having a browsing navigator to achieve an efficient browsing process in 3D information search space. This browsing navigator has the following major functions: ?1. Selection of features which determine the distance for visualization, in order to generate a uniform distribution of candidate data objects in the resulting space. ?2. Calculation of the location of the data objects in 2D space using the selected features. ?3. Construction of 3D browsing space by combining 2D spaces, in order to find the required data objects easily. ?4. Generation of the oblique views of 3D browsing space and data objects by reducing the overlap of data objects in order to make navigation easy for the user in 3D space. ?Examples of this browsing navigator applied to book data are shown. Received: 15 December 1997 / Revised: June 1999     

A user model neural network for a personal news service

User modelling has been widely applied to pedantic situations, where we are attempting to infer the user's knowledge. In teaching it is important to know that the user has mastered the elementary concepts before proceeding with the advanced topics. However, the application of user modelling to information retrieval demands a quite different type of user model. Here we construct a user model for browsing, where the user is uncertain of exactly which information he desires. This requires a more inexact and robust user model, that can quickly give guidance to the system. We propose a user model based on neural networks that can be constructed incrementally. Performance of the model shows some promise for this approach. We discuss the advantages and limitations of the approach and its implications for user modelling.     

面向Internet的个性化智能信息检索

文中提出了一个面向Ｉｎｔｅｒｎｅｔ的个性化智能信息检索系统,该系统的研究内容属目前智能信息检索领域的重要研究课题。系统采用分布式智能体Ａｇｅｎｔ技术、相关反馈学习算法和基于多用户个性化模式的层次智能信息滤波算法,并采用多模块之间尖线交互机制和个性化检索与集中游览相结合的检索方式等方法,有效地解决了现有系统在交互方式、自适应用户兴趣和信息源的变化、高效并行检索等方面的不足,该系统普通适用于Ｉｎｔｅｒ     

基于本体的主动元数据挖掘系统研究

传统网上信息检索是用户被动地依靠浏览超级链接网页而获取的。文中提出基于本体的主动元数据挖掘系统以及在果品领域的应用,在主动搜索、元数据生成、借助本体作用于数据的语义描述等方面,其效果是客观的。使得对信息数据的搜索从被动地获取到主动依靠计算机自动搜索;从依靠关键字作为查询依据到借助本体的作用获取语义描述的信息数据,进而提高了信息查询效率及查询的准确率,这也是当前信息检索研究的热门课题。实验证明,通过主动元数据挖掘实例可以实现语义的扩充,如同义、近义及上下位关系。同时也验证了本体对实施语义智能检索所带来的客观效果。     

A Lattice Conceptual Clustering System and Its Application to Browsing Retrieval

The theory of concept (or Galois) lattices provides a simple and formal approach to conceptual clustering. In this paper we present GALOIS, a system that automates and applies this theory. The algorithm utilized by GALOIS to build a concept lattice is incremental and efficient, each update being done in time at most quadratic in the number of objects in the lattice. Also, the algorithm may incorporate background information into the lattice, and through clustering, extend the scope of the theory. The application we present is concerned with information retrieval via browsing, for which we argue that concept lattices may represent major support structures. We describe a prototype user interface for browsing through the concept lattice of a document-term relation, possibly enriched with a thesaurus of terms. An experimental evaluation of the system performed on a medium-sized bibliographic database shows good retrieval performance and a significant improvement after the introduction of background knowledge.     

基于内容的视频检索系统在电子政务中的应用

实现信息化政务办公需要解决的一个问题是视频文档信息的检索与浏览。文中给出一个政务视频信息浏览和检索系统的方案,系统支持抽象层的视频信息浏览和基于示例图像的视频信息检索。系统分成两个主要部分:(1)视频内容结构化处理和抽象部分;(2)基于示例图像的视频信息检索部分。在部分(1)中,给出了一个基于颜色及目标轮廓变化特征进行非监督视频结构化和视频内容抽象的方法;在部分(2)中,首先对图像库中图像进行特征降维,然后进行聚类处理,这样降低了通过示例图像检索视频内容过程中相似性匹配运算的时间,提高了效率。     

Experimental comparison of navigation in a Galois lattice with conventional information retrieval methods

A controlled experiment was conducted comparing information retrieval using a Galois lattice structure with two more conventional retrieval methods: navigating in a manually built hierarchical classification and Boolean querying with index terms. No significant performance difference was found between Boolean querying and the Galois lattice retrieval method for subject searching with the three measures used for the experiment: user searching time, recall and precision. However, hierarchical classification retrieval did show significantly lower recall compared to the other two methods. This experiment suggests that retrieval using a Galois lattice structure may be an attractive alternative since it combines a good performance for subject searching along with browsing potential.     

A study on development of cognitive support features in recent ontology visualization tools

Ontologies are currently emerging as representation techniques for overlapping compatibility context domains. The continuing need for more effective information retrieval has lead to the creation of the notions of the semantic web and personalized information management. Subsequently, the need for effective ontology visualization for design, management and browsing has arisen. Several ontology visualization tools have come out to strengthen the users’ cognitive support. The primary goal of this paper is to present a survey on recently implemented ontology visualization tools and their contributions in the enrichment of users’ cognitive support. This work also presents the preliminary results of an evaluation of three visualization tools to determine the suitability of each method for end user applications where ontologies are used as browsing aids.