Weblogs have been growing quickly and transforming the World Wide Web toward a dynamic environment that Web pages are frequently updated. Although, Google has developed the search engine successfully in cope with the traditional web pages, it cannot effectively handle the dynamic blogspace. This research proposes an ontology-based semantic annotation framework based on concepts level in order to adaptively recommend blogrolls. The keyword match is being replaced by the semantic annotation technology of IE (Information Extraction) domain to implement a recommendation system. The objective of the recommendation system is to produce a recommended blogroll to the target weblog based on the weblog¡¦s concept affinities. Data sources of this research are from java.blogs community. The experiment of recommendation system is evaluated by Java programmers. The recommended blogrolls are evaluated by relevance that subjects score the degree of relevance between a target blogger and the recommended blogroll. The reliability of relevance among subjects is also tested. The results show that the recommended blogrolls obtain the middle level of relevance measured by subjects. The relevance evaluation of the recommended blogroll is independent from the concept density of the target blogger. The recommendation system is also reliable. Moreover, this study shed light on directions to improve the automated blogroll recommendation.