Both phrases and Boolean queries have a long history in information retrieval, particularly in commercial systems. In previous work, Boolean queries have been used as a source of phrases for a statistical retrieval model, This work, like the majority of research on phrases, resulted in little improvement in retrieval effectiveness, In this paper, we describe an approach where phrases identified in natural language queries are used to build structured queries for a probabilistic retrieval model. Our results show that using phrases in this way can improve performance, and that phrases that are automatically extracted from a natural language query perform nearly as well as manually selected phrases.

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The use of phrases and structured queries in information retrieval

A graphical condition builder is provided that presents a graphical representation of a search query. In an embodiment, the graphical condition builder presents a graphical and numerical preview indicating the size of the expected query results set. In an embodiment, a graphical preview is provided that includes graphical preview portions having a shape suggestive of a funnel. In an embodiment, the graphical condition builder supports formulating queries for both relational and multidimentional databases. In an embodiment, the graphical condition builder displays a textual indication of the type of logical operation being performed. In an embodiment, the graphical condition builder determines the type of logical operator to apply depending on the relative location of icons representing filter objects. In an embodiment, order dependent filters are available to the user. In an embodiment, the search query is represented by query steps, and multiple filter objects may be contained in each query step.

Graphical condition builder for facilitating database queries

This paper introduces a novel representation, called the InfoCrystal, that can be used as a visualization tool as well as a visual query language to help users search for information. The InfoCrystal visualizes all the possible relationships among N concepts. Users can assign relevance weights to the concepts and use thresholding to select relationships of interest. The InfoCrystal allows users to specify Boolean as well as vector-space queries graphically. Arbitrarily complex queries can be created by using the InfoCrystals as building blocks and organizing them in a hierarchical structure. The InfoCrystal enables users to explore and filter information in a flexible, dynamic and interactive way. >

InfoCrystal: A visual tool for information retrieval

We present a new linguistic approach to the construction of terminological feedback for use in interactive query refinement. The method exploits the tendency for key domain concepts within result sets to participate in families of semantically related lexical compounds. We outline an algorithm for computing a ranked list of result set “themes” and describe a web application, the Paraphrase Search Assistant, designed to make use of the theme extraction algorithm to support a recognition-based, iterative information seeking dialog.

The paraphrase search assistant: terminological feedback for iterative information seeking

In this paper we outline a research program for computational linguistics, making extensive use of text corpora. We demonstrate how a semantic framework for lexical knowledge can suggest richer relationships among words in text beyond that of simple co-occurrence. The work suggests how linguistic phenomena such as metonymy and polysemy might be exploitable for semantic tagging of lexical items. Unlike with purely statistical collocational analyses, the framework of a semantic theory allows the automatic construction of predictions about deeper semantic relationships among words appearing in collocational systems. We illustrate the approach for the acquisition of lexical information for several classes of nominals, and how such techniques can fine-tune the lexical structures acquired from an initial seeding of a machine-readable dictionary. In addition to conventional lexical semantic relations, we show how information concerning lexical presuppositions and preference relations can also be acquired from corpora, when analyzed with the appropriate semantic tools. Finally, we discuss the potential that corpus studies have for enriching the data set for theoretical linguistic research, as well as helping to confirm or disconfirm linguistic hypotheses.

Lexical semantic techniques for corpus analysis

This paper describes the design of a direct manipulation user interface for Boolean information retrieval. Intended to overcome the difficulties of manipulating explicit Boolean queries as well as the “black box” drawbacks of so-called natural language query systems, the interface presents a two-dimensional graphical representation of a user's natural language query which not only exposes heuristic query transformations performed by the system, but also supports query reformulation by the user via direct manipulation of the representation. The paper illustrates the operation of the interface as implemented in the AI-STARS full-text information retrieval system.

B. Alvey

Papers

A direct manipulation interface for boolean information retrieval via natural language query