Ontology, as a representation of shared conceptualization for variety of specific domains, is the core of the semantic web. Concept hierarchy is one of the most popular backbones of ontology which organizes the concepts according to hyponymy relationships, and stores massive entities as the instances of the concepts. An open concept hierarchy, e.g., Wikipedia, always needs to be constantly updated by adding new entities and concepts. In this paper, we propose an automatic solution for ontology update by inserting new entities and generating new concepts for concept hierarchy. The method only requires very limited information of new entity, i.e., the attributes of each entity. The solution is based on a hybrid strategy synthesizing the benefits from the structure of the concept tree and the content of the attributes. The content of the attributes is used to measure the similarity between an entity and a concept. The structure of the concept tree is used to determine which concepts need to be measured. During similarity measurement, the solution also synthesizes the statistical and rule-based factors. The effectiveness of the proposed method is verified by the experiments extending the Chinese and English Wikipedia concept hierarchy with new entities and concepts.

Automatic Update of Ontology Concept Hierarchy with New Entity Insertion and New Concept Generation Based on Semantic Measurement

Incidents of public security have an ascendant trend in recent years all over the world, and it is more important to understand the correlation of different kinds of public security incidents. With the popularization of the Internet, numerous web messages can provide resources to do that. However, an important challenge is that the web messages are often heterogeneous and unstructured. In this paper, we propose a methodology to extract events from noisy web messages automatically. Then, based on the essence and the propagation features of event ontologies, we analyze the correlation between three typical kinds of public security incidents in China. With a heterogeneous dataset containing microblog messages and news reports during 2011-2014, the case study shows that our methodology can locate the security event on timeline with an error less than 1 day. Furthermore, the analysis from multiple views not only reveals the correlation between different kinds of public security event, but also reveals the difference between the heterogeneous resources of news report and microblog.

A Case Study of Mining and Correlation Analysis of Public Security Events in Heterogeneous and Unstructured Web Messages

A Case Study of Mining and Correlation Analysis of Public Security Events in Heterogeneous and Unstructured Web Messages.

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Automatic Update of Ontology Concept Hierarchy with New Entity Insertion and New Concept Generation Based on Semantic Measurement

A Case Study of Mining and Correlation Analysis of Public Security Events in Heterogeneous and Unstructured Web Messages

A Case Study of Mining and Correlation Analysis of Public Security Events in Heterogeneous and Unstructured Web Messages.