While advances have been made in structuring, indexing and retrieval of multimedia documents, we propose to study the unexplored problematics of information retrieval on heterogeneous media sets composed of written and spoken documents. The coverage of modalities in retrieved results seems to be an important part of the user’s information need. We show that this problematic is not satisfied by ...

Traditional information retrieval systems use query words to identify relevant documents. In difficult retrieval tasks, however, one needs access to a wealth of background knowledge. We present a method that uses Wikipedia-based feature generation to improve retrieval performance. Intuitively, we expect that using extensive world knowledge is likely to improve recall but may adversely affect pr...

Passage Retrieval is a crucial step in question answering systems, one that has been well researched in the past. Due to the vocabulary mismatch problem and independence assumption of bag-of-words retrieval models, correct passages are often ranked lower than other incorrect passages in the retrieved list. Whereas in previous work, passages are reranked only on the basis of syntactic structures...

This paper reports our participation in the INEX 2008 AdHoc Retrieval track. We investigated the effect of multiword terms on retrieval effectiveness in an interactive query expansion (IQE) framework. The IQE approach is compared to a state-of-the-art IR engine (in this case Indri) implementing a bag-of-word query and document representation, coupled with pseudo-relevance feedback (automatic qu...

Bag-of-visual words (BOVW) is a local feature based framework for content-based image and video retrieval. Its performance relies on the discriminative power of visual vocabulary, i.e. the cluster set on local features. However, the optimisation of visual vocabulary is of a high complexity in a large collection. This paper aims to relax such a dependence by adapting the query generative model t...

As a first step to the instance search task, we employed several existing image retrieval methods in combination (local feature matching, region matching, and global feature matching), according to the type and property of query images. The best run in this approach was ranked 23rd of 42 as regards the average precision result. Keywords; PCA-SURF; Bag of Features; Color histogram; Haar-Wavelet;...

A case report is presented of intra-mural gallbladder carcinoma discovered incidentally after laparoscopic cholecystectomy who subsequently developed abdominal wall recurrence at the epigastric exit port, and axillary lymph node metastases. Possible preventative steps for tumour dissemination and a management plan if incidental carcinoma is diagnosed is discussed. The use of a non-porous retrie...

Natural Language Processing (NLP) for Information Retrieval has always been an interesting and challenging research area. Despite the high expectations, most of the results indicate that successfully using NLP is very complex. In this paper, we show how Support Vector Machines along with kernel functions can effectively represent syntax and semantics. Our experiments on question/answer classifi...

In this thesis, we present approaches to image retrieval, object recognition, and discriminative models. For image retrieval, we evaluate a large variety of different descriptors and answer the questions how descriptors can be combined and which descriptor should be chosen according to which criterion. We suggest a set of local descriptors that have been used successfully for object recognition...

Text classification in the medical domain is a real world problem with wide applicability. This paper investigates extensively the effect of text representation approaches on the performance of medical document classification. To accomplish this objective, we evaluated seven different approaches to represent real word medical documents. The text representation approaches investigated in this pa...