<Emphasis Type="Italic">I-Quest</Emphasis>: an <Emphasis Type="Italic">i</Emphasis>ntelligent <Emphasis Type="Italic">que</Emphasis>ry <Emphasis Type="Italic">st</Emphasis>ructuring based on user browsing feedback for semantic retrieval of video data

In spite of significant improvements in video data retrieval, a system has not yet been developed that can adequately respond to a user’s query. Typically, the user has to refine the query many times and view query results until eventually the expected videos are retrieved from the database. The complexity of video data and questionable query structuring by the user aggravates the retrieval process. Most previous research in this area has focused on retrieval based on low-level features. Managing imprecise queries using semantic (high-level) content is no easier than queries based on low-level features due to the absence of a proper continuous distance function. We provide a method to help users search for clips and videos of interest in video databases. The video clips are classified as interesting and uninteresting based on user browsing. The attribute values of clips are classified by commonality, presence, and frequency within each of the two groups to be used in computing the relevance of each clip to the user’s query. In this paper, we provide an intelligent query structuring system, called I-Quest, to rank clips based on user browsing feedback, where a template generation from the set of interesting and uninteresting sets is impossible or yields poor results.

Content-based retrieval of Flash™ movies: research issues,generic framework,and future directions

As a prevailing web media format, nowadays Flash™ movies are created, delivered, and viewed by over millions of users in their daily experiences with the Internet. However, issues regarding the indexing and retrieval of Flash movies are unfortunately overlooked by the research community, which severely restrict the utilization of the extremely valuable Flash resource. A close examination reveals that the intrinsic complexity of a Flash movie, including its heterogeneous media components, its dynamic nature, and user interactivity, makes content-based Flash retrieval a host of research issues not thoroughly addressed by the existing techniques. As the first endeavor in this area, we propose a generic framework termed as FLAME (FLash Access and Management Environment) embodying a 3-layer structure that addresses the representation, indexing, and retrieval of Flash movies by mining and understanding of the movie content. An experimental prototype for Flash retrieval is implemented to verify the feasibility and effectiveness of FLAME, and future research directions on Flash management and retrieval are discussed in details.

Design information retrieval: a thesauri-based approach for reuse of informal design information

Information is integral to the engineering design process, and gaining access to design knowledge is critical to effective design decision-making. This paper considers the indexing and retrieval of informal, unstructured information captured from electronic design logbooks. One of the key observations of informal design information is its evolutionary nature over time. While this characteristic makes informal information a rich source for reuse, it also makes it difficult to employ traditional information retrieval (IR) approaches. The work described in this paper is based on a framework developed specifically for the information handling requirements of designers. This manual method for indexing information is adapted to meet the evolutionary nature of design through the development of thesauri for design context. Several approaches to building thesauri are examined, including manual and automated methods. It is found that manual methods provide a high level of IR performance, but also have high overhead requirements. Machine methods, however, may provide a viable, low overhead alternative.

Multi‐level reranking approach for bug localization

Bug fixing has a key role in software quality evaluation. Bug fixing starts with the bug localization step, in which developers use textual bug information to find location of source codes which have the bug. Bug localization is a tedious and time consuming process. Information retrieval requires understanding the programme's goal, coding structure, programming logic and the relevant attributes of bug. Information retrieval (IR) based bug localization is a retrieval task, where bug reports and source files represent the queries and documents, respectively. In this paper, we propose BugCatcher, a newly developed bug localization method based on multi‐level re‐ranking IR technique. We evaluate BugCatcher on three open source projects with approximately 3400 bugs. Our experiments show that multi‐level reranking approach to bug localization is promising. Retrieval performance and accuracy of BugCatcher are better than current bug localization tools, and BugCatcher has the best Top N, Mean Average Precision (MAP) and Mean Reciprocal Rank (MRR) values for all datasets.     

MISS: A Generic Model for MetaInformation SubSystems

This paper presents an approach to a flexible model for building an indexing subsystem based on metadata: the MetaInformation Subsystem (MISS). The MISS model consists of a software architecture, a system architecture, and an information model. The software architecture relies on a model (based on four levels: database, storage & retrieval, functional core, and application) used for the development of applications for information systems to search in and populate a database. The system architecture consists of a Browsing Application and a Populating Application, both built on top of a Metadata Database via the proposed software architecture. The Browsing Application is in charge of managing the user's interaction with the subsystem (navigation, search, and retrieval), whereas the Populating Application provides a mechanism to insert metadata and data views into the MISS databases. Finally, the proposed information model (the Metadata Information Model—MIM) consists of the metadata content, its structure, and the representation model, being in connection with the MPEG-7 standardisation work and providing impact to this Forum. In order to validate it, MISS has been used in the implementation of the Browsing and Retrieval System of the HYPERMEDIA ACTS 361 Project Continuous Audiovisual Market in Europe (publicly demonstrated in several workshops and in Telecom Americas 2000), obtaining very good results in terms of functionality, flexibility and reliability.     

Bayesian network based business information retrieval model

The quality of business information can significantly affect the operation level of enterprise. This paper analyses the problem of business information retrieval (BIR). A Bayesian Network Based business information retrieval model (BN-BIRM) is proposed by means of Bayesian network (BN) and information retrieval (IR) theory and a method for query adaptation is presented. In this model the customized query requirement of enterprise (CQR) is expressed in terms of the predefined illustrative documents related to business domain. The similarities between the documents and the query are evaluated with the conditional probabilities among the nodes in the BN. In the experiments, BN-BIRM is compared with the Belief Network model based on vector space model (VSM) ranking strategy and the Inference Network model based on TF-IDF ranking strategy. The experimental results show that BN-BIRM is effective for collecting business information on a large scale.

智能协作信息技术在信息检索中的应用

针对Internet信息资源的特点和信息检索系统的现状,提出一个应用智能协作信息技术进行Internet信息检索的完整的解决方案,该智能信息检索系统应用了三类智能主体,即用户接口主体、信息处理主体和信息搜索主体,分别实现个性化的智能游览器、网上信息（主要是文档）的分析处理以及信息的搜索。分析了系统的基本结构作主要工作原理,并对系统实现进行了初步的讨论。     

Vocal Access to a Newspaper Archive: Assessing the Limitations of Current Voice Information Access Technology

This paper presents the design and the current prototype implementation of an interactive vocal Information Retrieval system that can be used to access articles of a large newspaper archive using a telephone. The implementation of the system highlights the limitations of current voice information retrieval technology, in particular of speech recognition and synthesis. We present our evaluation of these limitations and address the feasibility of intelligent interactive vocal information access systems.     

Efficient parallel Text Retrieval techniques on Bulk Synchronous Parallel (BSP)/Coarse Grained Multicomputers (CGM)

In this paper, we present efficient, scalable, and portable parallel algorithms for the off-line clustering, the on-line retrieval and the update phases of the Text Retrieval (TR) problem based on the vector space model and using clustering to organize and handle a dynamic document collection. The algorithms are running on the Coarse-Grained Multicomputer (CGM) and/or the Bulk Synchronous Parallel (BSP) model which are two models that capture within a few parameters the characteristics of the parallel machine. To the best of our knowledge, our parallel retrieval algorithms are the first ones analyzed under these specific parallel models. For all the phases of the proposed algorithms, we analytically determine the relevant communication and computation cost thereby formally proving the efficiency of the proposed solutions. In addition, we prove that our technique for the on-line retrieval phase performs very well in comparison to other possible alternatives in the typical case of a multiuser information retrieval (IR) system where a number of user queries are concurrently submitted to an IR system. Finally, we discuss external memory issues and show how our techniques can be adapted to the case when processors have limited main memory but sufficient disk capacity for holding their local data.

An empirical analysis of information retrieval based concept location techniques in software comprehension

Concept location, the problem of associating human oriented concepts with their counterpart solution domain concepts, is a fundamental problem that lies at the heart of software comprehension. Recent research has attempted to alleviate the impact of the concept location problem through the application of methods drawn from the information retrieval (IR) community. Here we present a new approach based on a complimentary IR method which also has a sound basis in cognitive theory. We compare our approach to related work through an experiment and present our conclusions. This research adapts and expands upon existing language modelling frameworks in IR for use in concept location, in software systems. In doing so it is novel in that it leverages implicit information available in system documentation. Surprisingly, empirical evaluation of this approach showed little performance benefit overall and several possible explanations are forwarded for this finding.

Information retrieval:a view from the Chinese IR community

During a two day strategic workshop in February 2018,22 information retrieval researchers met to discuss the future challenges and opportunities within the field.The outcome is a list of potential research directions,project ideas,and challenges.This report describes the major conclusions we have obtained during the workshop.A key result is that we need to open our mind to embrace a broader IR field by rethink the definition of information,retrieval,user,system,and evaluation of IR.By providing detailed discussions on these topics,this report is expected to inspire our IR researchers in both academia and industry,and help the future growth of the IR research community.     

A multi-agent platform for content-based image retrieval

Efficient and possibly intelligent image retrieval is an important task, often required in many fields of human activity. While traditional database indexing techniques exhibit a remarkable performance in textual information retrieval current research in content-based image retrieval is focused on developing novel techniques that are biologically motivated and efficient. It is well known that humans have a remarkable ability to process visual information and to handle the volume and complexity of such information quite efficiently. In this paper, we present a content-based image retrieval platform that is based on a multi-agent architecture. Each agent is responsible for assessing the similarity of the query image to each candidate image contained in a collection based on a specific primitive feature and a corresponding similarity criterion. The outputs of various agents are integrated using one of several voting schemes supported by the system. The system’s performance has been evaluated using various collections of images, as well as images obtained in specific application domains such as medical imaging. The initial evaluation has yielded very promising results.

Analyzing the efficacy of using digital ink devices in a learning environment

There has been increased interest on the impact of mobile devices such as PDAs and Tablet PCs in introducing new pedagogical approaches and active learning experiences. We propose an intelligent system that efficiently addresses the inherent subjectivity in student perception of note taking and information retrieval. We employ the idea of cross indexing the digital ink notes with matching electronic documents in the repository. Latent Semantic Indexing is used to perform document and page level indexing. Thus for each retrieved document, the user can go over to the relevant pages that match the query. Techniques to handle problems such as polysemy (multiple meanings of a word) in large databases, document folding and no match for query are discussed. We tested our system for its performance, usability and effectiveness in the learning process. The results from the exploratory studies reveal that the proposed system provides a highly enhanced student learning experience, thereby facilitating high test scores.

Reasoning about Textual Similarity in a Web-Based Information Access System

The degree to which information sources are pre-processed by Web-based information systems varies greatly. In search engines like Altavista, little pre-processing is done, while in knowledge integration systems, complex site-specific wrappers are used to integrate different information sources into a common database representation. In this paper we describe an intermediate point between these two models. In our system, information sources are converted into a highly structured collection of small fragments of text. Database-like queries to this structured collection of text fragments are approximated using a novel logic called WHIRL, which combines inference in the style of deductive databases with ranked retrieval methods from information retrieval (IR). WHIRL allows queries that integrate information from multiple Web sites, without requiring the extraction and normalization of object identifiers that can be used as keys; instead, operations that in conventional databases require equality tests on keys are approximated using IR similarity metrics for text. This leads to a reduction in the amount of human engineering required to field a knowledge integration system. Experimental evidence is given showing that many information sources can be easily modeled with WHIRL, and that inferences in the logic are both accurate and efficient.     

基于推理网络的文本检索模型

在研究现有文本信息检索技术的基础上,设计了基于推理网络的文本检索模型.提出一种改进的推理算法,以实现从文档观察事件到索引词出现事件的推理,使新模型可以更全面地利用文本数据信息.最后通过一个推理网络实例来说明实现推理的数学过程.     

基于Web的信息智能获取方法

The increasing stream of Web information available makes it ever more desirable of network users to retrieval interesting information efficiently.Obviously,AI can be made a good use in the information retrieval area.In this paper,the Intelligent Search Engine,Intelligent Browser,Intelligent Agent and Intelligent Information Push are introduced.Then the related key techniques are presented.At last,a framework of Intelligent Information Push System is discussed.     

基于本体的智能信息检索系统

近年来,基于本体的智能信息检索系统已成为智能信息检索系统领域最为活跃的研究方向之一.如何利用本体进一步提高其检索性能和智能性,成为基于本体的智能信息检索系统的主要研究目标.从面向过程的角度,对近几年基于本体的智能信息检索系统的研究进展进行了综述,对其框架、所需本体知识的获取和使用、关键技术、性能评测等进行了前沿概括、比较和分析.最后,对基于本体的智能信息检索系统有待深入研究的难点和热点进行了展望.     

Stream segregation algorithm for pattern matching in polyphonic music databases

As music can be represented symbolically, most of the existing methods extend some string matching algorithms to retrieve musical patterns in a music database. However, not all retrieved patterns are perceptually significant because some of them are, in fact, inaudible. Music is perceived in groupings of musical notes called streams. The process of grouping musical notes into streams is called stream segregation. Stream-crossing musical patterns are perceptually insignificant and should be pruned from the retrieval results. This can be done if all musical notes in a music database are segregated into streams and musical patterns are retrieved from the streams. Findings in auditory psychology are utilized in this paper, in which stream segregation is modelled as a clustering process and an adapted single-link clustering algorithm is proposed. Supported by experiments on real music data, streams are identified by the proposed algorithm with considerable accuracy.

Evolution of the Information-Retrieval System for Blind and Visually-Impaired People

Blind and visually-impaired people face many problems in interacting with information retrieval systems. State-of-the-art spoken language technology offers potential to overcome many of them. In the mid-nineties our research group decided to develop an information retrieval system suitable for Slovene-speaking blind and visually-impaired people. A voice-driven text-to-speech dialogue system was developed for reading Slovenian texts obtained from the Electronic Information System of the Association of Slovenian Blind and Visually Impaired Persons Societies. The evolution of the system is presented. The early version of the system was designed to deal explicitly with the Electronic Information System where the available text corpora are stored in a plain text file format without any, or with just some, basic non-standard tagging. Further improvements to the system became possible with the decision to transfer the available corpora to the new web portal, exclusively dedicated to blind and visually-impaired users. The text files were reformatted into common HTML/XML pages, which comply with the basic recommendations set by the Web Access Initiative. In the latest version of the system all the modules of the early version are being integrated into the user interface, which has some basic web-browsing functionalities and a text-to-speech screen-reader function controlled by the mouse as well.