Abstract. 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.

An important information access problem arises when the user is confronted with a very large number of documents that have been retrieved in response to a query. In this paper we explore the use of a technique, called Scatter/Gather, for the navigation of large collections of retrieved documents. Scatter/Gather clusters the documents into semantically coherent groups on-the-fly and presents descriptive summaries of the groups to the user. These groups can be used in several ways: to identify useful subsets of documents to be perused with other tools, to eliminate subsets whose contents appear nonrelevant, or to select promising document subsets for reclustering into more refined groups. This paper describes the Scatter /Gather algorithm and illustrates its application to retrieval results via two examples. Introduction If a user of an information access system issues a query that retrieves a very large number of documents, that user cannot be expected to have the time and patience to ...

The recent advances in Formal Concept Analysis (FCA) together with the major changes faced by modern Information Retrieval (IR) provide new unprecedented challenges and opportunities for FCA-based IR applications. The main advantage of FCA for IR is the possibility of creating a conceptual representation of a given document collection in the form of a document lattice, which may be used both to improve the retrieval of specific items and to drive the mining of the collection’s contents. In this paper, we will examine the best features of FCA for solving IR tasks that could not be easily addressed by conventional systems, as well as the most critical aspects for building FCA-based IR applications. These observations have led to the development of CREDO, a system that allows the user to query Web documents and see retrieval results organized in a browsable concept lattice. This is the second major focus of the paper. We will show that CREDO is especially useful for quickly locating the documents corresponding to the meaning of interest among those retrieved in response to an ambiguous query, or for mining the contents of the documents that reference a given entity. An on-line version of the system is available for testing at

In this paper we present a comprehensive approach to automatic organization and hybrid navigation of text databases. An organizing stage first builds a particular lattice representation of the data, through text indexing followed by lattice clustering of the indexed texts. The lattice representation, then, supports the navigation stage of the system, a visual retrieval interface that combines three main retrieval strategies: browsing, querying, and bounding. Browsing and querying are used to search the retrieval space, bounding is used to restrict it based on the information that users have, or get during their interaction with the system. We show that such a hybrid paradigm permits high flexibility in trading off information exploration and retrieval and, in addition, has good retrieval performance. We compared information retrieval using lattice-based hybrid navigation with conventional Boolean querying. The results of an experiment conducted on two medium-sized bibliographic databases showed that the performance of lattice retrieval was comparable to or better than Boolean retrieval

We present a two-stage system for information exploration and retrieval. The first stage, named GALOIS, organizes the information contained into a database into a particular lattice structure; the second stage, named ULYSSES, is a visual interface to access the structure built in the earlier stage. In this paper we focus on the latter. ULYSSES is based on a tight integration of traditional and novel user interaction paradigms that can be seen as a search&bound approach to information retrieval. The user may search the retrieval space by browsing or querying, but he or she may also bound the retrieval space by specifying constraints that the information contained in it has to satisfy. These interaction modes can be naturally combined to produce a hybrid retrieval strategy that best reflects the user goals and his/her domain knowledge. The retrieval effectiveness of our system has been tested in an experiment on subject searching where it compared favourably with respect to a Boolean retrieval system.

In this paper we present a comprehensive approach to conceptual structuring and intelligent navigation of text databases. Given any collection of texts, we first automatically extract a set of index terms describing each text. Next, we use a particular lattice conceptual clustering method to build a network of clustered texts whose nodes are described using the index terms. We argue that the resulting network supports an hybrid navigational approach to text retrieval - implemented into an actual user interface - that combines browsing potentials with good retrieval performance. We present the results of an experiment on subject searching where this approach outperformed a conventional Boolean retrieval system.