Chinese-English Cross-Lingual Information Retrieval in.

Query Expansion Phd Thesis

This thesis proposes and evaluates methods that aim at improving MCR effectiveness over the baseline of fulltext retrieval. We hypothesize that this objective can be achieved by utilizing controlled vocabularies of biomedical concepts for query expansion and concept-based retrieval. The latter represents case descriptions and queries as vectors.

Query Expansion Phd Thesis

The thesis investigates how persons in an enterprise organisation can be ranked in response to a query, so that those persons with relevant expertise to the query topic are ranked first. The expertise areas of the persons are represented by documentary evidence of expertise, known as candidate profiles. The statement of this research work is that the expert search task in an enterprise setting.

Query Expansion Phd Thesis

In this thesis, we propose a new approach to Chinese-English Biomedical cross-lingual information retrieval (CLIR) using query expansion based on the eCMeSH Tree, a Chinese-English ontology extended from the Chinese Medical Subject Headings (CMeSH) Tree. The CMeSH Tree is not designed for information retrieval (IR), since it only includes heading terms and has no term weighting scheme for.

Query Expansion Phd Thesis

This method implements the query expansion model. Specified by: score in class QueryExpansionModel Parameters: withinDocumentFrequency - double The term frequency in the X top-retrieved documents. termFrequency - double The term frequency in the collection. Returns: double The query expansion weight using he complete Kullback-Leibler divergence.

Query Expansion Phd Thesis

The potential and actual effectiveness of interactive query expansion. PhD thesis. (1988). Towards interactive query expansion. (1995). User-choices: a new yardstick for the evaluation of ranking algorithms for interactive query expansion. Information processing and management. To submit an update or takedown request.

Query Expansion Phd Thesis

This research considers the ongoing challenge of semantics-based search from the perspective of how to exploit Semantic Web languages for search in the current Web environment. The purpose of the PhD was to use ontology-based query expansion (OQE) to improve search effectiveness by increasing search precision, i.e. retrieving relevant documents in the topmost ranked positions in a returned.

Query Expansion Phd Thesis

We propose a novel method of query expansion for Language Modeling (LM) in Information Retrieval (IR) based on the similarity of the query with sentences in the top ranked documents from an initial retrieval run. In justification of our approach, we argue that the terms in the expanded query obtained by the proposed method roughly follow a Dirichlet distribution which, being the conjugate.

Query Expansion Phd Thesis

Results dominated by noise. 3. A significant gap between the low-level features and the semantics of the query. In our thesis, the first barrier is overcome by employing a simple block-based visual features which outperforms a method based on MPEG-7 features specially at early precision (precision of the top results). For the second obstacle, lists from words semantically weighted according to.

Query Expansion Phd Thesis

The PhD student will be welcomed into the Spoken Language Processing group at LIMSI located in Orsay (91400). Context of the thesis The PhD thesis will take place in the context of the MEERQAT project that aims to tackle the problem of analyzing ambiguous visual and textual content by learning and combining their representations and by taking into account the existing knowledge about entities.

Query Expansion Phd Thesis

Each examiner is asked to provide a written report with feedback about your thesis. Examiners are requested to return their written reports within: 4 weeks for an MPhil, or; 5 weeks for a PhD. You will receive your examination reports only when both examiners have completed and returned their reports and the Dean has determined the outcome. Following the receipt of these reports you will then.

Query Expansion Phd Thesis

Efthimiadis EN. Interactive query expansion and relevance feedback for document retrieval systems. PhD thesis, City University, London, UK, 1992 Google Scholar.

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