Retrieving with good sense

Although always present in text, word sense ambiguity only recently became regarded as a problem to information retrieval which was potentially solvable. The growth of interest in word senses resulted from new directions taken in disambiguation research. This paper first outlines this research and surveys the resulting efforts in information retrieval. Although the majority of attempts to improve retrieval effectiveness were unsuccessful, much was learnt from the research. Most notably a notion of under what circumstance disambiguation may prove of use to retrieval

Reflections on Excavating Archaeological Grey Literature: and on the Challenges in Information Extraction

The largely unpublished reports generated by commercial or “rescue” archaeology, commonly known as “grey literature” contain a great deal of untapped information, highly relevant to the research and analysis of archaeological evidence. The presentation unfolds experiences and challenges in using Natural Language Processing techniques for "unlocking" and surfacing information from unstructured textual input, delivering structured outputs which enable new information access methods, based on linking worded representations to ontological definitions and formalisations for the purposes of information retrieval from heterogeneous data sources. The role of Named Entity Recognition, Relation Extraction, Negation Detection, and Word-Sense Disambiguation is presentedin connection to a semantic annotation and automatic metadata generation endeavour, which spanned over ten years and two research projects, focusing on English, Dutch and Swedish grey literature

A Word Sense-Oriented User Interface for Interactive Multilingual Text Retrieval

In this paper we present an interface for supporting a user in an interactive cross-language search process using semantic classes. In order to enable users to access multilingual information, different problems have to be solved: disambiguating and translating the query words, as well as categorizing and presenting the results appropriately. Therefore, we first give a brief introduction to word sense disambiguation, cross-language text retrieval and document categorization and finally describe recent achievements of our research towards an interactive multilingual retrieval system. We focus especially on the problem of browsing and navigation of the different word senses in one source and possibly several target languages. In the last part of the paper, we discuss the developed user interface and its functionalities in more detail

Sense resolution properties of logical imaging

The evaluation of an implication by Imaging is a logical technique developed in the framework of modal logic. Its interpretation in the context of a “possible worlds” semantics is very appealing for IR. In 1994, Crestani and Van Rijsbergen proposed an interpretation of Imaging in the context of IR based on the assumption that “a term is a possibleworld”. This approach enables the exploitation of term– term relationshipswhich are estimated using an information theoretic measure. Recent analysis of the probability kinematics of Logical Imaging in IR have suggested that this technique has some interesting sense resolution properties. In this paper we will present this new line of research and we will relate it to more classical research into word senses

Preliminary results in tag disambiguation using DBpedia

The availability of tag-based user-generated content for a variety of Web resources (music, photos, videos, text, etc.) has largely increased in the last years. Users can assign tags freely and then use them to share and retrieve information. However, tag-based sharing and retrieval is not optimal due to the fact that tags are plain text labels without an explicit or formal meaning, and hence polysemy and synonymy should be dealt with appropriately. To ameliorate these problems, we propose a context-based tag disambiguation algorithm that selects the meaning of a tag among a set of candidate DBpedia entries, using a common information retrieval similarity measure. The most similar DBpedia en-try is selected as the one representing the meaning of the tag. We describe and analyze some preliminary results, and discuss about current challenges in this area