This year, like in 2006, we use a collection of about 160000 full-text articles. The proposed task is a passage retrieval task. Several measures are applied on the returned data: passage mean average precision, document mean average precision, aspect mean average precision. This year, our efforts concentrated on combining knowledge-driven methods on top of a standard vectorspace retrieval appro...

We performed the full experiments, using our network implementation of component probabilistic indexing and retrieval model. Documents were enhanced with a list of semi-automatically generated two-word phrases, and queries with automatic Boolean expressions. An item self-learning procedure was used to initiate network edge weights for retrieval. Initial results submitted were above median for a...

Textual information is becoming increasingly available in electronic forms. Users need tools to sift through non-relevant information and retrieve only those pieces relevant to their needs. The traditional methods such as Boolean operators and key terms have somehow reached their limitations. An emerging trend is to combine the traditional information retrieval and artificial intelligence techn...

Document Retrieval is the computerized process of producing a relevance ranked list of documents in response to an inquirer’s request by comparing their request to an automatically produced index of the documents in the system. Everyone uses such systems today in the form of web-based search engines. While evolving from a fairly small discipline in the 1940s, to a large, profitable industry tod...

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...

We study the problem of efficient dissemination of textual information over wide-area networks. Our dissemination architecture utilises middle-agents and sophisticated matching algorithms. The data model and query language is based on the well-known Boolean model from Information Retrieval. The main focus of this paper is the problem of matching incoming documents with submitted user profiles. ...

Web page categorization is an approach for improving precision and efficiency of information retrieval on the web by filtering out irrelevant pages. Current approaches to information filtering based on categorization assume the existence of a single classification hierarchy used for filtering. In this paper, we address the problem of filtering information categorized according to different clas...

For ranked retrieval, we relied on a statistical language model to compute query/document similarity values. Hiemstra and de Vries describe such a linguistically motivated probabilistic model and explain how it relates to both the Boolean and vector space models [4]. The model has also been cast as a rudimentary Hidden Markov Model [13]. Although the model does not explicitly incorporate invers...

Search Engine is a Web-page retrieval tool. Nowadays Web searchers utilize their time using an efficient search engine. To improve the performance of the search engine, we are introducing a unique mechanism which will give Web searchers more prominent search results. In this paper, we are going to discuss a domain specific Web search prototype which will generate the predicted Web-page list for...

NICTA (National ICT Australia) participated in the Medical Records track of TREC 2011 with seven automatic runs. The main techniques used in our submissions involved using Boolean retrieval for filtering, query transformation, and query expansion. Evaluation of our best run ranks our submissions higher than the median of all systems for this track, and stands at rank seven among 109 automatic r...