This study investigates the use and effectiveness of an advanced information retrieval (IR) system (IN-QUERY). 64 novice IR system users were studied in their use of a baseline version of INQUERY compared with one of three experimental versions, each offering a different level of interaction with a relevance feedback facility for automatic query reformulation. Results, in an information filtering task, indicate that: these subjects, after minimal training, were able to use the baseline system reasonably effectively; availability and use of automatic relevance feedback increased retrieval effectiveness significantly; and increased opportunity for user interaction with and control of relevance feedback made the interactions more efficient and usable while maintaining or increasing effectiveness.

Stemming is used in many information retrieval (IR) systems to reduce variant word forms to common roots. It is one of the simplest applications of natural language processing to IR, and one of the most effective in terms of user acceptance and consistent, though small, retrieval improvements. Current stemming techniques do not, however, reflect the language use in specific corpora and this can lead to occasional serious retrieval failures. We propose a technique for using corpus-based word variant co-occurrence statistics to modify or create a stemmer. The experimental results generated using English newspaper and legal text and Spanish text demonstrate the viability of this technique and its advantages relative to conventional approaches. Categories and Subject Descriptors: H.3.1. [Information Storage and Retrieval]: Content Analysis and Indexing -- indexing methods; linguistic processing; H.3.3. [Information Storage and Retrieval]: Information Search and Retrieval -- query f...

As retrieval systems become more oriented towards end-users, there is an increasing need for improved methods to evaluate their effectiveness. We performed a task-ori-ented assessment of two MEDLINE searching systems, one which promotes traditional Boolean searching on hu-man-indexed thesaurus terms and the other natural lan-guage searching on words in the title, abstract, and index-ing terms. Medical students were randomized to one of the two systems and given clinical questions to answer. The students were able to use each system successfully, with no significant differences in questions correctly answered, time taken, relevant articles retrieved, or user satisfaction between the systems. This approach to evaluation was successful in measuring effectiveness of system use and demonstrates that both types of systems can be used equally well with minimal training.

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The accurate formulation of boolean expressions is a notorious problem in programming languages and database query tools. This paper studies the ways that untrained users naturally express and interpret queries, revealing some of the underlying reasons why this task is so difficult. Among the study's findings are: people interpret the word AND to mean either conjunction or disjunction depending on context, the scope to which they attribute the word NOT depends on whether the subsequent operator is AND or OR, and they often ignore parenthesis. Therefore, relying on these words and symbols for query formulation will result in poor usability. A tabular query form is proposed that avoids the need to name the operators, provides a clear distinction between conjunction and disjunction, and makes

Push-based data delivery requires knowledge of user interests for making scheduling, bandwidth allocation, and routing decisions. Such information is maintained as user profiles. We propose a new incremental algorithm for constructing user profiles based on monitoring and user feedback. In contrast to earlier approaches, which typically represent profiles as a single weighted interest vector, we represent user profiles as multipleinterest vectors, whose number, size, and elements change adaptively based on user access behavior. This flexible approach allows the profile to more accurately represent complex user interests. Although there has been significant research on user profiles, our approach is unique in that it can be tuned to trade off profile complexity and quality. This feature, together with its incremental nature, makes our method suitable for use in large-scale information filtering applications such as push-based WWW page dissemination. We evaluate the method by experimentally investigating its ability to categorize WWW pages taken from Yahoo! categories. Our results show that the method can provide high filtering effectiveness with modest profile sizes and can effectively adapt to changes in users’ interests. 1.

A new laboratory-based method for the evaluation of Boolean queries in free-text searching of full-text databases is proposed. The method is based on a controlled formulation of inclusive query plans, on an automatic conversion of query plans into a set of elementary queries, and on composing optimal queries at varying operational levels by combining appropriate sub-sets of elementary queries. The method is based on the idea of reverse engineering, and exploits full relevance data of documents to find the query performing optimally within given operational constraints. The proposed

CH-8092 Z"urich (Switzerland)

As online document collections continue to expand, both on the Web and in proprietary environments, the need for duplicate detection becomes more critical. Few users wish to retrieve search results consisting of sets of duplicate documents, whether identical duplicates or close matches. Our goal in this work is to investigate the phenomenon and determine one or more approaches that minimize its impact on search results. Recent work has focused on using some form of signature to characterize a document in order to reduce the complexity of document comparisons. A representative technique constructs a ‘fingerprint ’ of the rarest or richest features in a document using collection statistics as criteria for feature selection. One of the challenges of this approach, however, arises from the fact that in production environments, collections of documents are always changing, with

We have built a hybrid Case-Based Reasoning (CBR) and Information Retrieval (IR) system that generates a query to the IR system by using information derived from CBR analysis of a problem situation. The query is automatically formed by submitting in text form a set of highly relevant cases, based on a CBR analysis, to a modified version of INQUERY's relevance feedback module. This approach extends the reach of CBR, for retrieval purposes, to much larger corpora and injects knowledge-based techniques into traditional IR. 1 Introduction One strength of Case-Based Reasoning (CBR) systems is the ability to reason about a problem case and perform highly intelligent problem-solving, such as the generation of legal arguments or detailed operational plans [9]. In particular, CBR systems have at their core the ability to retrieve highly relevant cases. However, CBR systems are limited by the availability of cases actually represented in their case bases. Among current case-based reasoning syst...