## Ontology-Based Information Behaviour to Improve Web Search  
**[PERSON] \({}^{\star}\) and [PERSON]**  
Department of Informatics, Systems and Communication-DISCo, University of Milano-Bicocca, V.le Sarca 336-14, 20126, Milano, Italy; E-Mail: [EMAIL_ADDRESS]  
\({}^{\star}\) Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS];  
Tel. : +39 0264487917; Fax: +39 0264487880. _Received: 24 September 2010; in revised form: 11 October 2010 / Accepted: 13 October 2010 / Published: 18 October 2010_  
**Abstract:** Web Search Engines provide a huge number of answers in response to a user query, many of which are not relevant, whereas some of the most relevant ones may not be found. In the literature several approaches have been proposed in order to help a user to find the information relevant to his/her real needs on the Web. To achieve this goal the individual Information Behavior can been analyzed to 'keep' track of the user's interests. _Keeping_ information is a type of Information Behavior, and in several works researchers have referred to it as the study on what people do during a search on the Web. Generally, the user's actions (e.g., how the user moves from one Web page to another, or her/his download of a document, _etc._) are recorded in Web logs. This paper reports on research activities which aim to exploit the information extracted from Web logs (or query logs) in personalized user ontologies, with the objective to support the user in the process of discovering Web information relevant to her/his information needs. Personalized ontologies are used to improve the quality of Web search by applying two main techniques: query reformulation and re-ranking of query evaluation results. In this paper we analyze various methodologies presented in the literature aimed at using personalized ontologies, defined on the basis of the observation of Information Behaviour to help the user in finding relevant information. **Keywords:** keeping information; ontologies; query reformulation; re-rankingIntroduction  
In the last few years there has been an exponential growth of the information available on the Web. The difficulty of locating information relevant to the user's needs is becoming a 'hot' and crucial problem, and a great deal of research is addressing this topic [1, 2]. People mainly use Web search engines as an access point to relevant information on the Internet. Unfortunately, a search engine produces several results in response to a user query, with the consequence that the truly relevant results are not always retrieved. In the literature, in order to face this unsatisfying situation, one of the suggested solutions is related to the contextualization of a user's Web search. The objective is to personalize the behaviour of Web search engines [2]. Indeed, the results produced by a search engine for a given query are the same, independent of the user and the context in which the user made the request. The main idea is to understand what the context is surrounding a Web-query during a user session: in the literature several proposals have been defined for this [3]. Possible solutions are related to _query-specific contexts_, and they include: (i) _context around query_ and (ii) _context within query_[4]. The former specifies the environment of a query, such as the domain of interest, while the latter refers to context words within the query [4]. The problem of personalization has also been faced in several studies of Information Behaviour. In [PERSON]'s model of information behaviour [5] the context of the information need is based on the personal context of a user where information seeking and searching are jointly considered at different stages of a search session. In particular, the personal context of a user is defined by collecting the information _acquired and organized over time and in response to a range of stimuli_[6]. On the Web, the search context may be defined by considering the information collected over time after several user's queries.