RIAO Conference 

About: RIAO Conference is an academic conference. The conference publishes majorly in the area(s): Search engine indexing & Document retrieval. Over the lifetime, 148 publications have been published by the conference receiving 3426 citations.

The TREC spoken document retrieval track: a success story

Abstract: This paper describes work within the NIST Text REtrieval Conference (TREC) over the last three years in designing and implementing evaluations of Spoken Document Retrieval (SDR) technology within a broadcast news domain. SDR involves the search and retrieval of excerpts from spoken audio recordings using a combination of automatic speech recognition and information retrieval technologies. The TREC SDR Track has provided an infrastructure for the development and evaluation of SDR technology and a common forum for the exchange of knowledge between the speech recognition and information retrieval research communities. The SDR Track can be declared a success in that it has provided objective, demonstrable proof that this technology can be successfully applied to realistic audio collections using a combination of existing technologies and that it can be objectively evaluated. The design and implementation of each of the SDR evaluations are presented and the results are summarized. Plans for the 2000 TREC SDR Track are presented and thoughts about how the track might evolve are discussed.

A taxonomy of musical genres

Abstract: The recent progress of Electronic Music Distribution creates a natural pressure for fine-grained musical metadata. This metadata is needed to provide music distribution services which are able to cope with the mere size of music catalogues, and the desire of users to access music titles by similarity. In this context, we describe a project of a global music title metadatabase, and focus in the particular "genre" descriptor. We analyze existing taxonomies of musical genre as found in the music industry and on the Internet, and stress on their inconsistencies. We describe a novel music genre taxonomy based on a few guiding principles, and report on the process of building this taxonomy.

Comparative evaluation of a natural language dialog based system and a menu driven system for information access: a case study

Abstract: This paper describes the evaluation of a natural language dialog based navigation system (HappyAssistant) that helps users access e-commerce sites to find relevant information about products and services. The prototype system leverages technologies in natural language processing and human computer interaction to create a faster and more intuitive way of interacting with websites, especially for the less experienced users. The result of a comparative study shows that users prefer the natural language enabled navigation two to one over the menu driven navigation. In addition, the study confirmed the efficiency of using natural language dialog in terms of the number of clicks and the amount of time required to obtain the relevant information. In the case study, comparing to the menu driven system, the average number of clicks used in the natural language system was reduced by 63.2% and the average time was reduced by 33.3%.

An annotation tool for web browsers and its applications to information retrieval

Abstract: With bookmark programs, current Web browsers provide a limited support to personalize the Web. We present a new Web annotation tool which uses the Document Object Model Level 2 and Dynamic HTML to deliver a system where speed and privacy are important issues. We report on several experiments showing how annotations improve document access and retrieval by providing user-directed document summaries. Preliminary results also show that annotations can be used to produce user-directed document clustering and classification.

A statistical word-level translation model for comparable corpora

Abstract: In this paper, we present a model of statistical word-level mapping for comparable corpora. The approach is based on the assumption that if two terms have close distributional profiles, their corresponding translations' distributional profiles should be close in a comparable corpus. The proposed model is described. A preliminary investigation on intralanguage comparable corpora is laid out. The preliminary results are >92% accurate, suggesting the feasibility of the model. The model needs to undergo some improvements and should be tested cross linguistically before assessing its significance.