## 5 Conclusions and Future Works  
Web search engines provide a huge number of answers in response to a user query with the consequence that a user cannot always find the results relevant to his/her information needs. In order to overcome this unsatisfying situation, a possible solution is to analyze the behaviour of a user during a search session, namely (1) to study the interactions of a user with search engines, and/or (2) to study the actions that he/she performs visiting Web pages. With the first case, the terms of a user's queries are stored into query log files; whereas in the second case, information such as the identifier of a user, URLs clicked for each query or actions such as save, print, copy, etc. related to a part of a Web page are stored in Web log files. All these files are analyzed in order to understand what the user's interests are, and thus to define ad-hoc the profile. This profile is used to improve the quality of a user's search. In this paper, we have investigated the use of ontologies, aimed at defining user profiles (called _ontological user profiles_). Ontologies allow to give a semantic organization to the information recorded in query and Web log files. In this short review, some works aimed at the use of a personal ontology have been discussed in order to face two typical Information Retrieval problems: query reformulation and results re-ranking. Most works use ODP as the reference ontology to define a user profile. The ODP is used in three different ways. In the first case, ODP has been used as a semantic support to find a relation between concepts (e.g., extracted from the preferred documents or the visited Web pages), in the second case, some parts of the ODP structure have been identified to be relevant for the user, and in the last strategy, the user has directly selected the categories (concepts) of interest from the ODP. The benefits of adopting strategies to obtain personalized searches on the Web are well known. In this paper, our interest has been directed towards two main approaches, namely query expansion and result re-ranking, to personalize a user's search with the support of personalized ontologies. With the coming of the Web 2.0, the way to share and define data has changed. New services are provided to handle folksonomies, blogs, wikis, and so on. In the literature, several works have addressed the problem of exploring folksonomies for personalized search. The term _folksonomy_ is a combination of _folk_ and _taxonomy_ to describe the social classification phenomenon [80]. Folksonomy arises from the textual annotation of Web resources and is described as a shared collection of tags. A tag is a _free-text keyword_, and tagging is the process aimed at assigning tags to resources. As free-text keywords, tags do not have exact meaning and suffer from linguistic ambiguities. In current folksonomies there is no agreement on the representation on such a tagging. This means that each system uses a different format to publish its tagging data with the consequence of having a difficult interoperability between them. In [81] an overview and a comparison of several tag ontologies defined with the objective to have a unique semantic representation has been presented. In this field of research, the main objective is to propose new approaches for improving a user's search. In [80, 82, 83] strategies for re-ranking search results are presented, based on the definition of a user profile, obtained after the analysis of bookmarked documents. In particular, a user profile is defined with the tags associated to each bookmarked document with the basic assumption that a user bookmarks only relevant interests to him/her. Metadata about Web results are collected by the community of users submitting bookmarks to the bookmark systems defining the so-called _document profile_. The re-ranking phase is then obtained calculating the similarity between a user profile and a document profile.