Exploiting Ontology in web Personalization/Recommendation

International Journal of Innovative Technology and Exploring Engineering, 2019

The emerging web page development requires semantic applications with customized administrations. The proposed methodology presents a customized suggestion framework, which makes utilization of item representations and also client profiles created based on ontology. The domain ontology helps the recommender to improve the personalization: from one perspective, client’s interests are displayed in an increasingly powerful and precise route by applying an area based derivative technique; on the other side, the stemmer algorithm derived content- based filtering approach, gives an evaluation of resemblance among a thing and a client, upgraded by applying a semantic likeliness strategy. Recommender frameworks and web personalize were assumed by Web usage mining as a critical job. The proposed strategy is s successful framework dependent on ontology and web usage mining. Extricating highlights from web reports and building applicable ideas is the initial step of the methodology. At that po...

Web Intelligence and Agent Systems, 2003

As the number of Internet users and the number of accessible Web pages grows, it is becoming increasingly difficult for users to find documents that are relevant to their particular needs. Users must either browse through a large hierarchy of concepts to find the information for which they are looking or submit a query to a publicly available search engine and wade through hundreds of results, most of them irrelevant. The core of the problem is that whether the user is browsing or searching, whether they are an eighth grade student or a Nobel prize winner, the identical information is selected and it is presented the same way. In this paper, we report on research that adapts information navigation based on a user profile structured as a weighted concept hierarchy. A user may create his or her own concept hierarchy and use them for browsing Web sites. Or, the user profile may be created from a reference ontology by 'watching over the user's shoulder' while they browse. We show that these automatically created profiles reflect the user's interests quite well and they are able to produce moderate improvements when applied to search results.

International Journal of Computer Applications, 2013

In proposed system personalized ontology for web information retrieval is introduced: Specificity and Exhaustively. Specificity describes a subject's focus on a given keyword. Exhaustively restricts a subject's semantic space dealing with the topic. Personalized ontology framework is proposed for knowledge representation and reasoning over behavior of users. This framework learns user profiles from both a world knowledge base and user background knowledge. The world knowledge and user background information are used to attempt to discover and specify user background knowledge. From a world knowledge base (WordNet database) personalized ontology are constructed focusing on user occupation. Ontological framework provides a solution to emphasizing global and local knowledge in a single computational framework. We present a personalized user specific ontological framework using WordNet knowledge for web information retrieval which will help to present the relevant search result to the user.

Ontology is a paradigmatic for describing the knowledge and is used to verbalize profile of user in personalized web information collection. User profiles can be characterized by extracting knowledge from either a global repository or local repository. The global analysis makes use of global repository and produce effectual performance. The local analysis digs out user behavior from user background information. The user background knowledge can be better observed and represented if we put together global and local analysis. In this paper, a personalized ontology model is used to generate user profiles. This model observes profile of user from both global repository and local repository. The search results are more personalized and have on-topic specificity. The relevance and efficiency measures produce more accurate results. Hence this model is preferred for web information.

International Journal of Advanced Trends in Computer Science and Engineering

The World Wide Web is an interlinked collection of billions of documents formatted using HTML. The amount of web based information available has increased dramatically. How to gather useful information from the web has become a challenging issue for users. Therefore, the new technology is to be introduced that that will be helpful for the web information gathering Ontology as model for knowledge description and formalization is used to represent user profile in personalized web information gathering. Ontology is the model for knowledge description and formalization. However the information of user profiles represents patterns either global or local knowledge base information, according to our analysis many models represents global knowledge. In this paper ontology system is used to recognize and reasoning over user profiles, world knowledge base and user instance repositories. This work also compares the analysis of existing system and ontology with other research areas are more efficient to represent.

… Workshop on Context …, 2006

Combining traditional personalization techniques with novel knowledge representation paradigms, such as the ontologybased approach proposed in the Semantic Web field, is a challenging task. Personalization is a difficult problem when dealing with multimedia content and information retrieval, where context is increasingly acknowledged to be a key notion in order to make proper sense of user needs. This work focuses on contextualization within personalization in a multimedia environment. Towards that scope, we propose a novel contextual knowledge modeling scheme, and an approach for the dynamic, contextual activation of semantic user preferences to better represent user interests in coherence with ongoing user activities, e.g. in an interactive retrieval process. The application of this methodology is demonstrated using two user scenarios, and the performance results of a preliminary experiment are shown.

Proceedings of the ninth international conference on Information and knowledge management - CIKM '00, 2000

The publicly indexable Web contains an estimated 800 million pages, however it is estimated that the largest search engine contains only 300 million of these pages. As the number of Internet users and the number of accessible Web pages grows, it is becoming increasingly difficult for users to find documents that are relevant to their particular needs. Often users must browse through a large hierarchy of categories to find the information for which they are looking. To provide the user with the most useful information in the least amount of time, we need a system that uses each user's view of the world for classification. This paper explores a way to use a user's personal arrangement of concepts to navigate the Web. This system is built by using the characterizations for a particular site created by the Ontology Based Informing Web Agent Navigation (OBIWAN) system and mapping from them to the user's personal ontologies. OBIWAN allows users to explore multiple sites via the same browsing hierarchy. This paper extends OBIWAN to allow users to explore multiple sites via their own browsing hierarchy. The mapping of the reference ontology to the personal ontology is shown to have a promising level of correctness and precision.

Information Technology Journal, 2003

Abstract: As the number of available Web pages grows, users experience increasing difficulty finding documents relevant to their interests. One of the underlying reasons for this is that most search engines find matches based on keywords, regardless of their meanings. To ...

INTERNATIONAL JOURNAL OF ADVANCES IN SIGNAL AND IMAGE SCIENCES

In this research, we offer a customized-recommendation system that uses item representations and user profiles based on the ontologies that provide personalized services to semantic applications. To develop and implement the personalized-recommendation system, a system that uses the representations of the items and the user profiles based on the ontologies to provide the semantic applications with personalized services. Recommendation systems can use semantic reasoning capabilities to overcome present system limits and increase the quality of recommendations. The recommender makes use of domain ontologies to improve personalization: on the one hand, a domain-based inference method is used to model user interests more effectively and accurately; on the other hand, a semantic similarity method is used to improve the stemmer algorithm, which is used by our content-based filtering approach, which provides a measure of the affinity between an item and the user. In recommender systems and web personalization, Web Usage Mining is crucial. This study presents an effective recommender system based on ontology and web usage mining. The approach's first step is to extract features from online documents and build on related ideas. Then, they create an ontology for the website using the concepts and relevant terms retrieved from the records. The semantic similarity of web documents is used to group them into multiple semantic themes, each with its own set of preferences. The suggested solution incorporates ontology and semantic knowledge into Web Usage Mining and personalization procedures, as well as a stemming algorithm, and gets an overall accuracy of 90%.