Trivikram Immaneni

A Unified Approach to Retrieving Web Documents and Semantic Web Data

The Semantic Web seems to be evolving into a property-linked web of RDF data, conceptually divorced from (but physically housed in) the hyperlinked web of HTML documents. We discuss the Unified Web model that integrates the two webs and formalizes the structure and the semantics of interconnections between them. We also discuss the Hybrid Query Language which combines the Data and Information Retrieval techniques to provide a convenient and uniform way to retrieve data and documents from the Unified Web. We present the retrieval system SITAR and some preliminary results.

Selecting labels for news document clusters

This work deals with determination of meaningful and terse cluster labels for News document clusters. We analyze a number of alternatives for selecting headlines and/or sentences of document in a document cluster (obtained as a result of an entity-event-duration query), and formalize an approach to extracting a short phrase from well-supported headlines/sentences of the cluster that can serve as the cluster label. Our technique maps a sentence into a set of significant stems to approximate its semantics, for comparison. Eventually a cluster label is extracted from a selected headline/sentence as a contiguous sequence of words, resuscitating word sequencing information lost in the formalization of semantic equivalence.

Hybrid retrieval from the unified web

The goal of Semantic Web initiative is to make the semantics of Web content accessible to machines. The Semantic Web has been evolving into a web of data separate from the existing HTML web. Our work focuses on establishing and exploiting connections between the two webs, especially hyperlink connections from the HTML web pages to the Semantic Web nodes, so as to enhance both data and document retrieval. We propose the Unified Web model to integrate the two webs, and a hybrid query language to retrieve data and documents from the Unified Web. Specifically, the query language amalgamates graph-based reasoning over RDF with keyword-based search.

Integrated Retrieval from Web of Documents and Data

The Semantic Web is evolving into a property-linked web of data, conceptually different from but contained in the Web of hyperlinked documents. Data Retrieval techniques are typically used to retrieve data from the Semantic Web while Information Retrieval techniques are used to retrieve documents from the Hypertext Web. We present a Unified Web model that integrates the two webs and formalizes connection between them. We then present an approach to retrieving documents and data that captures best of both the worlds. Specifically, it improves recall for legacy documents and provides keyword-based search capability for the Semantic Web. We specify the Hybrid Query Language that embodies this approach, and the prototype system SITAR that implements it. We conclude with areas of future work.

A coherent query language for XML

Text search engines are inadequate for indexing and searching XML documents because they ignore metadata and aggregation structure implicit in the XML documents. On the other hand, the query languages supported by specialized XML search engines are very complex. In this paper, we present a simple yet flexible query language, and develop its semantics to enable intuitively appealing extraction of relevant fragments of information while simultaneously falling back on retrieval through plain text search if necessary. Our approach combines and generalizes several available techniques to obtain precise and coherent results.

Flexible querying of XML documents

Text search engines are inadequate for indexing and searching XML documents because they ignore metadata and aggregation structure implicit in the XML documents. On the other hand, the query languages supported by specialized XML search engines are very complex. In this paper, we present a simple yet flexible query language, and develop its semantics to enable intuitively appealing extraction of relevant fragments of information while simultaneously falling back on retrieval through plain text search if necessary. We also present a simple yet robust relevance ranking for heterogeneous document-centric XML.

An XML-Based Approach to Handling Tables in Documents

We explore application of XML technology for handling tables in legacy semistructured documents. Specifically, we analyze annotating heterogeneous documents containing tables to obtain a formalized XML Master document that improves traceability (hence easing verification and update) and enables manipulation using XSLT stylesheets. This approach is useful when table instances far outnumber distinct table types because the effort required to annotate a table instance is relatively less compared to formalizing table processing that respects table’s semantics. This work is also relevant for authoring new documents with tables that should be accessible to both humans and machines.