An emerging aspect in learning environment is to effectively retrieve learning materials from learning object repositories. An extension of the IEEE LOM standard with a domain ontology and automatic annotation for effective retrieval of learning objects is proposed. To make best use of learning objects outside the Learning Management System, we associate the learning materials with metadata pedagogic attributes such as prerequisite, type, difficulty level, importance, roles and significance. Automatic annotation of the learning object repository is developed in a semantic oriented approach. The techniques such as specific indexing for parsing the documents and using standard classification algorithms for automatic extraction with concept identification and significance for effective personalization is developed using domain ontology. The usage of Word Net based processing and the identification of learning objects based on the concept for text and media learning objects has proved effective using the domain ontology. The experimental results have proved better precision and recall using the combination of methods for effective personalization. The developed evaluating methods correlate with the scores of the topics and generally outperform the traditional term frequency inverse document frequency (TF-IDF) method. The proposed specific indexing method obtains the highest precision and recall of all. © IDOSI Publications, 2013.