<XML><RECORDS><RECORD><REFERENCE_TYPE>3</REFERENCE_TYPE><REFNUM>8417</REFNUM><AUTHORS><AUTHOR>Azzopardi,L.</AUTHOR><AUTHOR>Girolami,M.</AUTHOR><AUTHOR>Crowe,M.</AUTHOR></AUTHORS><YEAR>2005</YEAR><TITLE>Probabilistic Hyperspace Analogue to Language</TITLE><PLACE_PUBLISHED>Proceedings of the 28th Annual ACM Conference on Research and Development in Infomration Retrieval (SIGIR 2005)</PLACE_PUBLISHED><PUBLISHER>N/A</PUBLISHER><PAGES>575-576</PAGES><LABEL>Azzopardi:2005:8417</LABEL><KEYWORDS><KEYWORD>Language Model</KEYWORD></KEYWORDS<ABSTRACT>Song and Bruza [6] introduce a framework for Information Retrieval(IR) based on Gardenfor's three tiered cognitive model; Conceptual Spaces[4]. They instantiate a conceptual space using Hyperspace Analogue to Language (HAL[3] to generate higher order concepts which are later used for ad-hoc retrieval. In this poster, we propose an alternative implementation of the conceptual space by using a probabilistic HAL space (pHAL). To evaluate whether converting to such an implementation is beneficial we have performed an initial investigation comparing the concept combination of HAL against pHAL for the task of query expansion. Our experiments indicate that pHAL outperforms the original HAL method and that better query term selection methods can improve performance on both HAL and pHAL.</ABSTRACT></RECORD></RECORDS></XML>