Exploring Topic Difficulty in Information Retrieval Systems Evaluation

Evolution of Topic in Information Retrieval Systems

Thare are various systems using Boolean, vector and other models for representation of documents. Each of these models has limitations that do not allow the user to find all relevant documents. This paper describes the approach to retrieving of topic development based on aglomerative clustering. Standard methods of IR does not allow us such kind of queries for appropriate solution of informatio...

Topic by Topic Performance of Information Retrieval Systems

Abstract Formulation of topic properties is the goal of this paper. These properties are to be used in judging the difficulty of topics appropriate to the Text REtrieval Conference (TREC) ad hoc task. Applying statistical methods to both TREC-6 and TREC-7 information retrieval results, we identify topic pairs that exemplify topic properties useful in relating topic statements to system performa...

Exploring Topic-based Language Models for Effective Web Information Retrieval

The main obstacle for providing focused search is the relative opaqueness of search request—searchers tend to express their complex information needs in only a couple of keywords. Our overall aim is to find out if, and how, topic-based language models can leads to more effective web information retrieval. In this paper we explore retrieval performance of a topic-based model that combines topica...

Sensitivity of IR systems Evaluation to Topic Difficulty

The difficulty of the topics or queries is one of important factors in evaluating information retrieval (IR) systems. This paper analyzes the differences of system ranking affected by the topic difficulty using a test collection ’NTCIR-1,’ which is constructed for evaluating Japanese IR systems and composed of (1) the topics, (2) the document database, and (3) the lists of relevant judgments. F...

Topic Models in Information Retrieval