## 2 Use of Ontologies to Capture the Information Behaviour  
Today's search engines constitute an important search tool on the Web for many people; although search engines usually provide a huge numbers of answers, many of which are not relevant, some of the more interesting answers are not found. One of the reasons for this situation is that existing Web search engines are not able to _interpret_ the user's context (at least to some extent). To improve this situation it would be useful to give the systems the possibility to better understand the meaning of a user's query in order to produce better answers. The goal, in this case is to reduce the communication gap between humans and machines: _\"...interaction between people and computers requires essentially the same interpretative work that characterizes interaction between people\"_[14]. Ontologies have been used as a possible approach towards the above research direction; in fact, as they allow to represent the knowledge of a specific domain, ontologies can be used to help people and machines to communicate concisely by facilitating the information exchange based on semantics rather than just on syntax. An ontology is made up of concepts, instances, functions, relationships and axioms to provide a common understanding of the real world [15, 16, 17, 18]. With the support of ontologies, users and systems can communicate with each other through an easy information integration [19]. Ontologies can be employed not only to reduce the communication gap between humans and machines but also to formally represent the user's interests and context. The definition of a personalized ontology is aimed at representing the user's personal interests. Since generally a person has several interests, user profiles should be defined to represent the various user interests. For example, in [20] a user profile is proposed to represent the distinct interests related to a user. The use of an ontological language to formally define a user profile can offer an effective solution to this problem. For this reason, in several works, a personalized ontology is viewed like a user profile, named _ontological user profile_[21]. To understand the user intent of a Web search could in this context mean identifying the user's interest related to the query in the user ontology. Generally, an ontology can be defined either manually by experts of the considered domain or in a semi-automatic way by analyzing a specific source (domain-dependent) of information. In the literature two main approaches have been applied to define an ontological user profile: (1) by the use of general purpose ontologies (e.g., ODP), and (2) by personalized ontologies. In both cases, the ontology is used as a semantic support to identify user intentions. In [21] an example of a personalized ontology obtained from the ODP is presented. Figure 1 depicts a graphical representation of an ontological user profile where just a _portion_ of the knowledge is represented in the ODP. In particular, only the categories of user interest are automatically selected from the ODP after the analysis of the user's actions during a search session, and an importance score is associated with each concept (for more details see Section 3). In this quite simple representation the categories are linked through the taxonomic relation IS-A. In some Information Behaviour works, a personalized ontology is employed to provide a semantic organization to the information selected by the users within a search session. In this situation a personalized ontology is (semi-)automatically built after the analysis, for example, of Web log files. In [22] a domain model based on an ontology, named _Behavior Knowledge Base_, is defined by storing the information about all the significant actions performed by the user on the Web. Examples of significant user's actions are: accessing a Web page, downloading the preferred information, _etc._  
Once a personalized ontology has been defined, it is possible to use it in order to improve the user's search.