1. 1 Semantic Driven Hshing(SDH): An Ontology-based Search Scheme for Semantic Aware Network(SA Net) Chatree Sangpachatanaruk, Taieb Znati University of Pittsburgh 2004 IEEE 指導老師：許子衡 老師 報告學生：羅英辰

2. 2 Introdution(1) Structured P2P overlay networks have gained attention as a viable solution to effectively facilitate resource discovery and sharing in large scale net- works.  DHT ：  Advantages: Reducing considerably the searching overhead due to communication and routing.  Shortcomings: Its lack of support for location-based queries that go beyond perfect matching.

3. 3 Introdution(2) Semantic Aware Network (SA Net):To address the lim-itation of DHT-based structures and meet the design requirement of multiple key-mapping resource discovery scheme.

4. 4 SA Net Search Scheme(1) SA Net further enhances the DHT-based resource distribution scheme by using the unique identifier assigned to each ontology as a key to locate the overlay node responsible for maintaining the resource index associated with the underlying ontology.

5. 5 SA Net Search Scheme(2) To further explain the SDH-based resource discovery scheme, We consider an ontology that describes the concept of “telecommunication”, as depicted in Figure 1.

6. 6 SA Net Search Scheme(3) To ensure global consistency in semantic classifica- tion, SA Net must support a globally defined ontology map which represents the well-known concepts and which can be used to guide an SDH-based search query. To achieve this goal, SA Net uses an Wordnet lexical network, which referred to as OSN.  Ontology Semantic Network (OSN): Each node in OSN is assigned a numerical ID that is used as the hash input for an SDH-based search.

7. 7 Ontology_discovery(K): To get a ID which is assigned a numerical ID. Hash(A) : A is hashed to obtain the keys.

8. 8 Related Work Recent frameworks propose to use information retrieval techniques, namely vector space model (VSM), and latent semantic indexing (LSI), to obtain semantic representation from the textual information appearing in the resource and queries. Another approach uses XML techniques to generate semantic representation from metadata attributes. SA Net relies on the ontologies that capture the keywords’ meanings and semantic relations, which can be used to infer related resources more intuitively.