We propose a new method of processing general Boolean queries utilizing previous query results stored in a result cache in a mediator architecture. A simple but noble normalization form is developed to describe keyword-based Boolean queries and the content of the result cache. We propose Boolean query processing algorithms based on this form of presentation that utilizes the result cache. We sh...

The Internet-based recruiting platforms become a primary recruitment channel in most companies. While such platforms decrease the recruitment time and advertisement cost, they suffer from an inappropriateness of traditional information retrieval techniques like the Boolean search methods. Consequently, a vast amount of candidates missed the opportunity of recruiting. The recommender system tech...

The Internet caused a substantial impact on the recruitment process through the creation of erecruiting platforms that become a primary recruitment channel in most companies. While companies established job positions on these portals, job-seeker uses them to publish their profiles. E-recruitment platforms accomplished clear advantages for both recruiters and job-seekers by reducing the recruitm...

In state of the art Information Retrieval (IR) systems the most salient problem is to improve recall rates while retaining high precision. A simple recall enhancing technique which can be useful for even the simplest boolean retrieval systems is stemming. It is obvious that an information-seeker who is looking for texts about, for example, dogs is probably interested in a text which contains th...

Text search operations are used to locate and retrieve needed information from some text collection. In traditional information retrieval, text search is a means for identifying relevant documents [Salton83, Lee85]. By specifying selection criteria for the text of a document, the reader can choose a subset of a given set of documents. If the text collection is defined not as a set of documents,...

Indian Statistical Institute, Kolkata participated in TREC for the first time this year. We participated in TREC Legal Interactive task in two topics namely, Topic 301 and Topic 302. We reduced the size of the corpus by Boolean retrieval using Lemur 4.11 and followed it by a clustering technique. We chose members from each cluster (which we called seeds) for relevance judgement by the TA and as...

The vocabulary of the TREC Legal OCR collection is noisy and huge. Standard techniques for improving retrieval performance such as content-based query expansion are ineffective for such document collection. In our work, we focused on exploiting metadata using blind relevance feedback, iterative improvement from the reference Boolean run, and the effects of using terms from different topic field...

This paper describes participation of Dokuz Eylül University to WikipediaMM task at ImageCLEF2009. This year we concentrated on two main topics: First is about expansion of native document, term phrase selection and query expansion processes which is based on WordNet, WSD and WordNet similarity functions. The second is a new reranking approach with Boolean retrieval and CM based clustering. Exp...

In this paper we describe the implementation of an extreme variation to the inverted file scheme. The scheme supports a comprehensive set of Boolean search operators, down to the single character level. When combined with a heuristic document ranking algorithm it supports retrieval of raw XML data, using the embedded tags as search arguments. We tested the system against a set of XML queries an...