Formal models, usability and related work in IR (editorial for special edition)

The Glasgow IR group has carried out both theoretical and empirical work, aimed at giving end users efficient and effective access to large collections of multimedia data

Term Similarity-Based Query Expansion for Cross-Language Information Retrieval

. We propose a query expansion technique which is based on a statistical similarity measure among terms to improve the effectiveness of the dictionary-based cross-language information retrieval (CLIR) method. We employ a term similarity-based sense disambiguation technique proposed in our earlier work to enhance the accuracy of the dictionary-based query translation method. The query expansion technique is then applied to the translation of queries to further improve their retrieval performance. We demonstrate the effectiveness of the two techniques combined using queries in three languages, namely, German, Spanish, and Indonesian, to retrieve English documents from a standard TREC (Text Retrieval Conference) collection. The results of our experiments indicate that the term similarity-based techniques work better when there are more phrases in the queries. In addition, our results also re-emphasize other researchers' finding that phrase recognition and translation are criti..

A Digital Library Approach to the Reconstruction of Ancient Sunken Ships

Throughout the ages, countless shipwrecks have left behind a rich historical and technological legacy. In this context, nautical archaeologists study the remains of these boats and ships and the cultures that created and used them. Ship reconstruction can be seen as an incomplete jigsaw reconstruction problem. Therefore, I hypothesize that a computational approach based on digital libraries can enhance the reconstruction of a composite object (ship) from fragmented, incomplete, and damaged pieces (timbers and ship remains). This dissertation describes a framework for enabling the integration of textual and visual information pertaining to wooden vessels from sources in multiple languages. Linking related pieces of information relies on query expansion and improving relevance. This is accomplished with the implementation of an algorithm that derives relationships from terms in a specialized glossary, combining them with properties and concepts expressed in an ontology. The main archaeological sources used in this dissertation are data generated from a 17th-century Portuguese ship, the Pepper Wreck, complemented with information obtained from other documented and studied shipwrecks. Shipbuilding treatises spanning from the late 16th- to the 19th-centuries provide textual sources along with various illustrations. Additional visual materials come from a repository of photographs and drawings documenting numerous underwater excavations and surveys. The ontology is based on a rich database of archaeological information compiled by Mr. Richard Steffy. The original database was analyzed and transformed into an ontological representation in RDF-OWL. Its creation followed an iterative methodology which included numerous revisions by nautical archaeologists. Although this ontology does not pretend to be a final version, it provides a robust conceptualization. The proposed approach is evaluated by measuring the usefulness of the glossary and the ontology. Evaluation results show improvements in query expansion across languages based on Blind Relevance Feedback using the glossary as query expansion collection. Similarly, contextualization was also improved by using the ontology for categorizing query results. These results suggest that related external sources can be exploited to better contextualize information in a particular domain. Given the characteristics of the materials in nautical archaeology, the framework proposed in this dissertation can be adapted and extended to other domains