Word sense disambiguation: a survey <s> Information retrieval (IR): <s> It has often been thought that word sense ambiguity is a cause of poor performance in Information Retrieval (IR) systems. The belief is that if ambiguous words can be correctly disambiguated, IR performance will increase. However, recent research into the application of a word sense disambiguator to an IR system failed to show any performance increase. From these results it has become clear that more basic research is needed to investigate the relationship between sense ambiguity, disambiguation, and IR. <s> BIB001 </s> Word sense disambiguation: a survey <s> Information retrieval (IR): <s> Word sense ambiguity is recognized as having a detrimental effect on the precision of information retrieval systems in general and web search systems in particular, due to the sparse nature of the queries involved. Despite continued research into the application of automated word sense disambiguation, the question remains as to whether less than 90% accurate automated word sense disambiguation can lead to improvements in retrieval effectiveness. In this study we explore the development and subsequent evaluation of a statistical word sense disambiguation system which demonstrates increased precision from a sense based vector space retrieval model over traditional TF*IDF techniques. <s> BIB002
Resolving ambiguity in a query is the most vital issue in IR BIB001 BIB002 [20] [21] [22] [23] system. As for example, a word "depression" in a query may carry different meanings as illness, weather systems, or economics. So, finding the exact sense of an ambiguous word in a particular question before finding its answer is the most vital issue in this regard. Information extraction (IE) and text mining: WSD plays an important role for information extraction in different research works as Bioinformatics research, Named Entity recognition system, co-reference resolution etc.