An Ontology Like Model for gathering Personalized Web Information (original) (raw)

Personalized Ontology Model for Web Information Gathering

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.

Ontology based personalized web information gathering

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.

A personalized ontology model for web information gathering

IEEE Transactions on Knowledge and Data …, 2010

As a model for knowledge description and formalization, ontologies are widely used to represent user profiles in personalized web information gathering. However, when representing user profiles, many models have utilized only knowledge from either a global knowledge base or a user local information. In this paper, a personalized ontology model is proposed for knowledge representation and reasoning over user profiles. This model learns ontological user profiles from both a world knowledge base and user local instance repositories. The ontology model is evaluated by comparing it against benchmark models in web information gathering. The results show that this ontology model is successful. , after receiving his PhD degree from QUT in 2009. His research interests include ontology learning and mining, knowledge engineering, web intelligence, data mining, sentiment analysis and opinion mining, machine learning, and information retrieval.

An Ontology Model for Knowledge Representation over User Profiles

2014

The amount of information on the world wide web increases rapidly. But gathering the required information from the web has become the most challenging job in today's scenario. People are only interested in the relevant information from the web. The web information gathering systems before this satisfy the user's requirements by capturing their information needs. For this reason user profiles are created for user background knowledge representation and description. The user profiles represent the concepts models possessed by user while gathering the useful web information. The concept of Ontologies is utilized in personalized web information gathering which are called ontological user profiles or personalized ontologies. In this paper, an ontology model is proposed for representing the user background knowledge for personalized web information gathering. Personalized ontology attempts to improve the web information gathering performance by using ontological user profiles. The model constructs user personalized ontologies by extracting world knowledge from the Library of Congress Subject Headings system and discovering user background knowledge from user local instance repositories.

An Adapted Ontology Model for Web Information Gathering

Artificial Intelligent Systems and Machine Learning, 2013

For knowledge portrayal and formalization, ontologies are extensively used to represent user profiles in personalized web information gathering. When representing user profiles, many models have made use of only knowledge from either a global knowledge base or user local information. This paper is aimed at the simulation of mind maps representing the preferences, in a software system and thereby enhancing the efficiency of web information gathering for a person. An adapted ontology model is suggested for knowledge representation and reasoning over user profiles. This model uncovers ontological user profiles from both a world knowledge base and user local instance repositories which possess content based descriptors. Content based descriptors have through indication to the notions specified in a global knowledge base. The model gives valuable contributions to personalized ontology engineering and concept-based Web information gathering. The suggested knowledge-based model donates to improved designs of knowledge-based and personalized Web information gathering systems. A multidimensional method, Specificity is also offered to quantitatively examine these semantic relations in a single framework. Specificity (denoted spe) portrays a subject‟s hub on a given topic. This method intends to investigate the subjects and the strength of their relationships in ontology. The user information wants at the sentence level rather than the article level, and presented user profiles by the Conceptual Ontological Graph. From a world knowledge base, we make adapted ontologies by adopting user feedback on interesting knowledge.

Personalized Ontological Framework for Web Information Retrieval

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 mining for personalizedweb information gathering

Proceedings of the IEEE/WIC/ACM …, 2007

It is well accepted that ontology is useful for personalized Web information gathering. However, it is challenging to use semantic relations of "kind-of", "part-of", and "related-to" and synthesize commonsense and expert knowledge in a single computational model. In this paper, a personalized ontology model is proposed attempting to answer this challenge. A two-dimensional (Exhaustivity and Specificity) method is also presented to quantitatively analyze these semantic relations in a single framework. The proposals are successfully evaluated by applying the model to a Web information gathering system. The model is a significant contribution to personalized ontology engineering and concept-based Web information gathering in Web Intelligence.

Study on Ontology Model for Web Information Gathering

Web-based information available has increased dramatically. How to gather useful information from the web has become a challenging issue for users. Current web information gathering systems attempt to satisfy user requirements by capturing their information needs. For this purpose, user profiles are created for user background knowledge description. User profiles represent the concept models possessed by users when gathering web information. A concept model is implicitly possessed by users and is generated from their background knowledge. While this concept model cannot be proven in laboratories, many web oncologists have observed it in user behavior. Ontology mining discovers interesting and on-topic knowledge from the concepts, semantic relations, and instances in ontology. In this section, a 2D ontology mining method is introduced: Specificity and Exhaustively. Specificity (denoted spe) describes a subject’s focus on a given topic. Exhaustively restricts a subject’s semantic space dealing with the topic. This method aims to investigate the subjects and the strength of their associations in ontology. Our work assumes that all user local instance repositories have content-based descriptors referring to the subjects; however, a large volume of documents existing on the web may not have such content-based descriptors. For this problem, strategies like ontology mapping and text classification/clustering were suggested. The investigation will extend the applicability of the ontology model to the majority of the existing web documents and increase the contribution and significance of the present work. Keywords—Ontology, Web information, Web model, ontology mining, knowledge base.

A Personalized Ontology Model for High Performance in Web Information Retrieval

The number of Internet users and the number of accessible Web pages are ever increasing day by day. It is becoming difficult for users to find relevant documents to their interests or needs. Thus whole process of finding relevant document is becoming time consuming. In this paper, we report on research that attempt information retrieval based on a user profile. A user can create his own concept hierarchy and use them for web searching which attempts to reveal expected documents to user. Ontology models are used to represent user profiles in personalized web information retrieval process. Many models make use of any one of the global knowledge base or user local information for representing user profiles. We attempt a personalized ontology model for knowledge representation. This model uses ontological user profiles based on a world knowledge base and user local instance repositories. It is observed that superior representation of user profiles can be built by using user concept models and it is found that the ontology model improves performance of web information retrieval.

Exploiting Ontology in web Personalization/Recommendation

Web pages are personalized based on the characteristics (interests, social category, context, ...) of an individual. Personalization technology enables the lively insertion, customization or hint of content in any format that is pertinent to the individual user, based on the user " s implicit actions and inclinations, and explicitly given details. In this work, context is taken out from Ontology in terms of concepts. Ontology is utilized to recognize topics that might be of attention to a specific user. For example, the query " Python " will be expanded with " programming language " , for the users fascinated in computer programming language, and with " snake " , for the users fascinated in " wild life " .