Disambiguation strategies for cross-language information retrieval

This paper gives an overview of tools and methods for Cross-Language Information Retrieval (CLIR) that are developed within the Twenty-One project. The tools and methods are evaluated with the TREC CLIR task document collection using Dutch queries on the English document base. The main issue addressed here is an evaluation of two approaches to disambiguation. The underlying question is whether a lot of effort should be put in finding the correct translation for each query term before searching, or whether searching with more than one possible translation leads to better results? The experimental study suggests that the quality of search methods is more important than the quality of disambiguation methods. Good retrieval methods are able to disambiguate translated queries implicitly during searching

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

Sense-Based Arabic Information Retrieval Using Harmony Search Algorithm

Information Retrieval (IR) is a field of computer science that deals with storing, searching, and retrievingdocuments that satisfy the user need. The modern standard Arabic language is rich in multiple meanings (senses) for manywords and this is substantially due to lack of diacritical marks. The task for finding appropriate meanings is a key demand inmost of the Arabic IR applications. Actually, the successful system should not be interested only in the retrieval quality andoblivious to the system efficiency. Thus, this paper contributes to improve the system effectiveness by finding appropriatestemming methodology, word sense disambiguation, and query expansion for addressing the retrieval quality of AIR. Also, itcontributes to improve the system efficiency through using a powerful metaheuristic search called Harmony Search (HS)algorithm inspired from the musical improvisation processes. The performance of the proposed system outperforms the one inthe traditional system in a rate of 19.5% while reduces the latency in an approximate rate of 0.077 second for each query