4,226 research outputs found
A Vertical PRF Architecture for Microblog Search
In microblog retrieval, query expansion can be essential to obtain good
search results due to the short size of queries and posts. Since information in
microblogs is highly dynamic, an up-to-date index coupled with pseudo-relevance
feedback (PRF) with an external corpus has a higher chance of retrieving more
relevant documents and improving ranking. In this paper, we focus on the
research question:how can we reduce the query expansion computational cost
while maintaining the same retrieval precision as standard PRF? Therefore, we
propose to accelerate the query expansion step of pseudo-relevance feedback.
The hypothesis is that using an expansion corpus organized into verticals for
expanding the query, will lead to a more efficient query expansion process and
improved retrieval effectiveness. Thus, the proposed query expansion method
uses a distributed search architecture and resource selection algorithms to
provide an efficient query expansion process. Experiments on the TREC Microblog
datasets show that the proposed approach can match or outperform standard PRF
in MAP and NDCG@30, with a computational cost that is three orders of magnitude
lower.Comment: To appear in ICTIR 201
Investigating Retrieval Method Selection with Axiomatic Features
We consider algorithm selection in the context of ad-hoc information retrieval. Given a query and a pair of retrieval methods, we propose a meta-learner that predicts how to combine the methods' relevance scores into an overall relevance score. Inspired by neural models' different properties with regard to IR axioms, these predictions are based on features that quantify axiom-related properties of the query and its top ranked documents. We conduct an evaluation on TREC Web Track data and find that the meta-learner often significantly improves over the individual methods. Finally, we conduct feature and query weight analyses to investigate the meta-learner's behavior
Incorporation of two terminology projects into a system for information retrieval using NLP for term expansion
In this paper, we will discuss two medical terminology projects at the University College of Ghent, Faculty of translation studies, and the benefits of combining them to provide Dutch professionals and laymen with better access to information in biomedical databases. Our first project, the MeSH Termbase Project (MTB) is aimed at health care professionals, medical translators and also patients in need of language support. The main aim of our second project, the Multilingual Glossary of Technical and Popular Medical Terms, is the simplification of the terminology used in patient information leaflets
Servicing the federation : the case for metadata harvesting
The paper presents a comparative analysis of data harvesting and distributed computing as complementary models of service delivery within large-scale federated digital libraries. Informed by requirements of flexibility and scalability of federated services, the analysis focuses on the identification and assessment of model invariants. In particular, it abstracts over application domains, services, and protocol implementations. The analytical evidence produced shows that the harvesting model offers stronger guarantees of satisfying the identified requirements. In addition, it suggests a first characterisation of services based on their suitability to either model and thus indicates how they could be integrated in the context of a single federated digital library
Multilingual adaptive search for digital libraries
This paper describes a framework for Adaptive Multilingual Information Retrieval (AMIR) which allows multilingual resource discovery and delivery using on-the-fly machine translation of documents and queries. Result documents
are presented to the user in a contextualised manner. Challenges and affordances of both Adaptive and Multilingual IR, with a particular focus on Digital Libraries, are detailed. The framework components are motivated by a series of results from experiments on query logs and documents from The European Library. We conclude that factoring adaptivity and multilinguality aspects into the search process can enhance the user’s experience with online Digital Libraries
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