Configurable meta-search in the human resource domain

Abstract

Unemployment rate is increasing day by day and one of the causes of unemployment is problem in searching and distribution of jobs.<br />Traditional methods of job/employee search i.e. newspapers, advertising at job fairs, employment recruitment agencies and registering with search firms, lack the ability for search in the modern employment market. Traditional job search engines do not provide comprehensive coverage of the Web and suffer from low recall and precision. To overcome these problems, we propose a new configurable meta-search engine in the human resource domain to provide an ideal platform for meta-search provider and a job seeker. One of the important challenges in accessing heterogeneous and distributed data via a meta-search engine is schema/data matching and integration. We describe an approach to schema and data integration for meta-search engines that helps to resolve the syntactic, semantic and structural heterogeneity between multiple information sources. To achieve our main goal, we are concerned with techniques to support two key aspects of meta-search engines: i) meta-search engine creation by meta-search engine providers and ii) meta-search engine usage for information seekers. In this dissertation, our objective is to resolve semantic conflicts while accessing multiple search engines. Our approach is a hybrid one, in that we use multiple matching criteria and multiple matchers. We employ several element levels, structure levels and ontology based techniques during the integration process. A domain ontology serves as a global ontology and allows us to resolve semantic heterogeneity. The mappings derived are used to generate an integrated meta-search query interface, to support query processing in the meta-search engine, and to resolve semantic conflicts arising during result extraction from the source search engines. Experiments conducted in the job search domain show that our hybrid approach increases the correctness of matching during the automatic integration of source search interfaces. The system supports meta-search provider in the quick development of meta-search engines and is able to understand and integrate schemas from different job search engines semantically. The system helps the job seekers in a way that they do not need to spend their time to comb through large numbers of job sites and job results in searching for the relevant job. An important aspect of our meta-search in human resource domain is that it has been designed by applying semantic Web technologies. We provide the solutions for automatic integration of data, structures and processes in human resource domain into a meta-search by the use of our modelled domain ontology and multiple matchers. Our modelled domain ontology helps to understand the search results too.<br />Flexible and re-useable design patterns have been introduced for the creation process, usage process and different components of meta-search engine to help the meta-search provider and the information seeker.<br />Design patterns for different components of meta-search engine help the new developers to speed up the development process.<br />

Unemployment rate is increasing day by day and one of the causes of unemployment is problem in searching and distribution of jobs.<br />Traditional methods of job/employee search i.e. newspapers, advertising at job fairs, employment recruitment agencies and registering with search firms, lack the ability for search in the modern employment market. Traditional job search engines do not provide comprehensive coverage of the Web and suffer from low recall and precision. To overcome these problems, we propose a new configurable meta-search engine in the human resource domain to provide an ideal platform for meta-search provider and a job seeker. One of the important challenges in accessing heterogeneous and distributed data via a meta-search engine is schema/data matching and integration. We describe an approach to schema and data integration for meta-search engines that helps to resolve the syntactic, semantic and structural heterogeneity between multiple information sources. To achieve our main goal, we are concerned with techniques to support two key aspects of meta-search engines: i) meta-search engine creation by meta-search engine providers and ii) meta-search engine usage for information seekers. In this dissertation, our objective is to resolve semantic conflicts while accessing multiple search engines. Our approach is a hybrid one, in that we use multiple matching criteria and multiple matchers. We employ several element levels, structure levels and ontology based techniques during the integration process. A domain ontology serves as a global ontology and allows us to resolve semantic heterogeneity. The mappings derived are used to generate an integrated meta-search query interface, to support query processing in the meta-search engine, and to resolve semantic conflicts arising during result extraction from the source search engines. Experiments conducted in the job search domain show that our hybrid approach