International Journal of Emerging Technology and Advanced Engineering Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 3, Issue 4, April 2013) 282 Sense Disambiguation in Information Retrieval Rekha Jain 1 , Rupal Bhargava 2 , Sulochana Nathawat 3 , G.N Purohit 4 1, 2, 3, 4 Banasthali Vidyapith, Jaipur Abstract— Ambiguity is the main problem faced by the search engines. User while performing the search does not bother about the ambiguity that lies in search terms and expects the relevant result. Hence it is required by the search engine to resolve such ambiguities. In this paper we have discussed methods to solve ambiguity and resolve it. Also we have proposed an algorithm Dynamic Page Rank which is not only resolving the ambiguities but also rearranging the results according to user. Keywords— Word Sense Disambiguation, Lexical Ambiguity, Page Rank Algorithm, F-measure. I. INTRODUCTION Due to global exchange of information, there has been a rapid expansion in availability of online texts. It has been a great deal to manage such vast repository of text and provide access to end user for accessing this repository. User always expects to get the most appropriate results. The work of searching is done by the search engines. Search engines help the user to get appropriate results according to user needs. For this purpose they adopt various methods and algorithms to rank the results. But what when the search string is ambiguous? For example check can refer to term check mate and check can also refer to verification of something. The task of Information Retrieval (IR) becomes quite complicated; also user may not get what he/she actually wants. Hence it becomes important to resolve the ambiguity for the user to get accurate results. In this paper we will discuss about the ambiguity problem faced by the search engines and propose an algorithm to resolve such an ambiguity. II. INFORMATION RETRIEVAL Information Retrieval is a vast area of study which deals with the storage, organization, representation and access of data. It helps the user to find what he actually wants. Main task of IR is to estimate the degree to which documents in collection reflect the information given as a user query to the system. There are three steps to the whole procedure. Representation work of text objects is done, then search terms entered by user are matched or compared with these documents, and finally most relevant documents are extracted as per the search terms and evaluated. III. SENSE AMBIGUITY When a word, phrase or a sentence is open to more than one interpretation it is said to be ambiguous. There are two type of ambiguity: Syntactic and Semantic. A. Semantic Ambiguity When a word has more than one meaning it may result in semantic ambiguity. For e.g. Second can used as time representation or it can used to represent a position. B. Syntactic Ambiguity When structure of a sentence leads to more than one possible interpretation. For e.g. Ram ate cookies on the couch. This statement can have more than one meaning. One can be Ram ate cookies that were on the couch and another one can be Ram ate cookies sitting on the couch. We confront with ambiguities of natural language in daily use. However humans don’t find it much difficult to resolve such sense ambiguity. But for machine it is a great deal of work to resolve ambiguity. In machine disambiguation, syntax may be applied only when sentence is grammatically correct. In some cases, cues such as number of agreement between subject and object pair can also be applied. For the purpose of resolving sense ambiguity we use Word Sense Disambiguation. IV. WORD SENSE DISAMBIGUATION Word Sense Disambiguation is a task of identifying the correct meaning of a word in context at lexical level. It is a fundamental problem of Natural Language Processing. It is a field potentially used as a component of Machine Translation (MT) and Information Retrieval (IR). [8] In Information Retrieval, Word Sense Disambiguation can bring two kinds of benefits. One is Queries having ambiguous meaning which in turn affects the précised retrieval of results. Precision is a measure of the ability of the system to present only relevant items. Another is words in the query may be strongly related to the meaning of other words which are not present in the query. This will affect the recall of retrieval. Recall is the measure of the ability of a system to present all relevant items.