Use Of Information Retrieval Research Articles

Mobile agents and their use for information retrieval: a brief overview and an elaborate case study

Mobile agents emerged in the mid-1990s, and have raised considerable interest in the research community. The proponents associate several benefits with their use. However, there are still very few quantitative measurements to back the claimed benefits. This article is devoted to mobile agents and their use for information retrieval. We provide a brief overview and an elaborate case study. The overview introduces the concept of mobile agent, enumerates the claimed benefits, and reviews the hindrances to widescale deployment. It also discusses the state of the art of mobile-agent-based information retrieval, including the very few quantitative studies that exist. Our case study is on information retrieval from electronic calendars for multiparty event scheduling. Many events require the participation of several parties. Prior knowledge of the date when most (if not all) targeted participants are available is often a prerequisite for scheduling them. However, identifying this date can easily turn into a nightmare, especially when the number of targeted participants is large. Nowadays, electronic agendas (e.g., MS Outlook) are stored on servers. An application can access them, retrieve information on the availability of the targeted participants, and derive the date from the information. In the case study, a mobile agent is dispatched in the network, instead of retrieving the information using the client/server paradigm. The agent visits the servers, accesses the agendas, retrieves the information, and identifies the date. Finding a date suitable for several potential participants may require the rescheduling of some events that have been previously arranged by some participants. We propose the use of agents that act as the personal agents of the participants for the negotiation inherent to this rescheduling. The measurements we have made indicate clearly that the mobile-agent-based approach outperforms its client/server counterpart even when the latter is optimized. These results can easily be transposed to most information retrieval applications, and demonstrate, for this specific application domain, the performance benefit associated with mobile agents. We now dispatch a single agent in the network. In the future, we will dispatch several agents.

Stemming and n-grams in Spanish: an evaluation of their impact on information retrieval

At some stage, most of the models and techniques implemented in information retrieval use frequency counts of the terms appearing in documents and in queries. However, many words, since they are derived from the same stem, have very close semantic content. This makes a grouping of such variants under a single term advisable. Otherwise, dispersal occurs in the calculation of frequency of these terms and it also becomes difficult to compare queries and documents. On the other hand, there are notable differences between different languages in the way of forming derivatives and inflected forms, so that the application of specific techniques can produce unequal results according to the language of the documents and queries. A description is given of tests carried out for documents in Spanish, which involved some stemming techniques widely used in English, as well as the application of n-grams, and the results are compared.

INSYDER : information retrieval aspects of a business intelligence system

This paper presents a visual information seeking system for the WWW called INSYDER 1 . The aim of INSYDER is to find business information from the WWW. Information seeking - especially an the Web - is an imprecise process. Information seekers often have only a fuzzy understanding of how they can get the information they want. This paper focuses on the use of information retrieval and visualisation techniques of the INSYDER system to support the user in extracting information from the WWW, namely in formulating queries, refining and reviewing results.

A study of probability kinematics in information retrieval

We analyze the kinematics of probabilistic term weights at retrieval time for different Information Retrieval models. We present four models based on different notions of probabilistic retrieval. Two of these models are based on classical probability theory and can be considered as prototypes of models long in use in Information Retrieval, like the Vector Space Model and the Probabilistic Model. The two other models are based on a logical technique of evaluating the probability of a conditional called imaging; one is a generalization of the other. We analyze the transfer of probabilities occurring in the term space at retrieval time for these four models, compare their retrieval performance using classical test collections, and discuss the results. We believe that our results provide useful suggestions on how to improve existing probabilistic models of Information Retrieval by taking into consideration term-term similarity.

A User-Dependent Definition of the Information in Images and Its Use in Information Retrieval

Operational image databases are subsystems of systems which contain images, structured data, structured data completions, and algorithms, all relating to a particular real-world domain. Traditional notions of image similarity therefore need to be extended to handle retrieval of mixed datatypes. In this paper, we use the structured datatypes to describe a user's interests and background knowledge and then to ascribe a value to that user of the information in the system. The difference between the information values in two states of a system leads naturally to a user-dependent definition of the (dis) similarity between the states. These definitions restrict respectively to definitions of the value of information in an image, and of the (dis)similarity between two images. We show how this notion of similarity provides an integrated way of dealing with image and nonimage data, generalizing conventional classes of feature-based similarity measures and allowing for missing data. Because the measure depends on the data models and data in the structured part of the database as well as on image characteristics, the similarity between two images may change when nonimage data in the system are updated or extended. We illustrate using an example from a business domain.

Development of IR systems: New direction

The paper addresses a question of improving the quality of satisfaction of information need (IN) through the use of information retrieval (IR) systems. This improvement is achieved by more fully taking into account the characteristics of IN when developing IR systems. For this reason the characteristics of IN are investigated very carefully and on the basis of this analysis the paper proposes a new instrument in IR systems which takes into account different components of IN. Special attention is paid to the practical implementation of such IR systems. Using the goal component of IN as an example the paper demonstrates how to take this component into account in the process of IR system functioning, namely by using a list of tasks and requirements. It is shown that during the implementation of this list several problems have to be addressed and the paper discusses some possible solutions. The suggested methods and approaches are easily adaptable to any IR system and their realization is quite simple. The paper stresses the importance of this new direction in developing IR systems.

Conjunction, ellipsis, and other discontinuous constituents in the constituent object parser

The Constituent Object Parser (COP) is a domain independent syntactic parser developed for use in information retrieval and similar applications. Its purpose is to extract a simple hierarchical description of a phrase or sentence that can be used in very general pattern matching procedures to determine the structural similarity of sentences or phrases that contain equivalent terms. This paper discusses the mechanisms by which COP handles the problems of conjunction, ellipsis, and discontinuous constituents. These structures are usually particularly difficult to handle in a parser that does not employ domain knowledge or even general semantic knowledge. cop's mechanisms for these structures are directly tailored for, and, in part, even made possible by, the nature of the intended uses of the outputs by the information retrieval matching procedures.

Educational uses of a dynabook

The Dynabook personal computing concept, as introduced by the Xerox Learning Research Group (LRG) in the early 1970's, is a new communications tool based on the retrieval of dynamic information. Implementing the Dynabook concept is requiring several stages of computer hardware and software development. At each stage of developing an experimental (or ‘interim Dynabook’) system, we are studying its use for educational purposes by conducting computer programming classes for children ranging in age from 6 to 15 years and by implementing a number of laboratory situations for particular subject areas. Preliminary results of our studies have demonstrated the ease with which we can teach programming when it involves the combination of existing instructions in order to cause some computer-based effect. But more than the ability to combine existing instructions is needed in order to invent and construct a generally useful tool such as a graphical layout system or a text editor. These involve skills we typically associate with expert designers. Many of these skills are teachable, especially with the instructional assistance of a personal computer. Supported by several examples of laboratory situations that we have implemented, we propose a design curriculum based on three conceptual areas: process, symbolic representation, and methods of interpretation, especially with respect to the use of information retrieval as an aid in decision making. In the examples we have chosen to describe, the design skills exercised are: simple and conditional sequencing, rule or constraint specification, hypothesis testing and modelling. The particular situations cited are: programming in Smalltalk, computer-based animation, GameX (a game that involves programming by rule specification). ThingLab (a laboratory for describing physical or geometric objects) and a ‘kit’ for assembling event-driven simulations.

A hybrid framework for natural language processing of large data bases

At the Information Retrieval Research Laboratory we are working on combining techniques in common use in information retrieval with concepts from artificial intelligence to provide enhanced processing of large data bases. Information retrieval research has provided the inverted file, which indexes the occurrence of each word in a text file. Our system will include a complete inverted index as an underlying representation of the natural language text and will impose additional information structures on that index. Specifically, the index will include: information about the semantic function of words at each of their occurrences, linguistic knowledge connecting the vocabulary nodes, "fact nodes" attached to vocabulary nodes describing entities (e.g. people), and procedural knowledge needed to find facts and build fact nodes - attached to word nodes and functioning as word demons. The information structure will have some features of a semantic net, some of a network of frames. The procedural and linguistic knowledge attached to a vocabulary node will fill the function of an ATN segment that is attached to the sentence ATN when the associated word is recognized and will also be responsible for recognizing limited kinds of facts and attaching them as attributes to the appropriate entity.

Word segmentation by letter successor varieties

This paper describes a method for automatically segmenting words into their stems and affixes. The process uses certain statistical properties of a corpus (successor and predecessor letter variety counts) to indicate where words should be divided. Consequently, this process is less reliant on human intervention than are other methods for automated stemming. The segmentation system is used to construct stem dictionaries for document classification. Information retrieval experiments are then performed using documents and queries so classified. Results show not only that this method is capable of high quality word segmentation, but also that its use in information retrieval produces results that are at least as good as those obtained using the more traditional stemming processes.

The use of automatically-obtained keyword classifications for information retrieval

This report summarizes the work carried out on the automatic construction of keyword classifications and their use in information retrieval that we have carried out in the last eighteen months. It discusses the possible characteristics of such classifications, and potential ways of using them; and describes the various approaches to classification we have considered, in terms of an overall frame of reference in which several types of classification are distinguished. The results of experiments using a collection of documents and test requests obtained from the Aslib Cranfield project are presented, from which it can be concluded that automatic classifications which lead to noticeable improvements in retrieval performance over those obtainable with unclassified terms can be set up.