Weiyi Ge, Gong Cheng, Huiying Li, Yuzhong Qu Incorporating Compactness to Generate Term-Association View Snippets for Ontology Search Weiyi Ge, Gong Cheng, Huiying Li, Yuzhong Qu Accepted by Information Processing and Management

Snippet for Ontology Search Why need ontology search? Reuse Amount Why need snippet? Numerous ontologies Numerous triples/terms Reuse: enhance data interoperability, reduce cost and accelerate development progress

Requirements for Snippets 1. Semantic relations among terms are preferred

Requirements for Snippets 2. Direct relations or indirect but close relations are preferred

Requirements for Snippets 3. Compact

Requirements for Snippets Term association view Semantic relations among terms are preferred Direct relations or indirect but close relations are preferred Compact Bounded size Query relevant In summary, A good snippet for ontology search is a term-association view information unit within a bounded size that effectively summarizes the query result for human reading and judgment.

Outline Semantic relations among terms  term association graph (TAG) Close relations  maximal r-radius subgraph Compactness  group Steiner problem Size+relevance  assembly Evaluation

Outline Semantic relations among terms  term association graph (TAG) Close relations  maximal r-radius subgraph Compactness  group Steiner problem Size+relevance  assembly Evaluation

Term Association Graph RDF Sentence it makes no sense if RDF triples sharing common blank nodes are separated

Term Association Graph X(t1, t2, R) is a set of RDF sentences in R, in each of which there is a directed path connecting t1 and t2 whose arcs exclude rdf:type. Preference Preference of sentence: prefS(S) Preference of term association: prefX(X(t1,t2,R))=ΣprefS(S)

Term Association Graph

Term Association Graph

Outline Semantic relations among terms  term association graph (TAG) Close relations  maximal r-radius subgraph Compactness  group Steiner problem Size+relevance  assembly Evaluation

Maximal r-Radius Subgraph Motivation Relations with close distances Size restriction Reduce the graph scale Defintion r-Radius Subgraph Gi is a subgraph of G and the radius of Gi is less than or equal to r. Maximal r-Radius Subgraph No other r-Radius subgraph is its supergraph.

Maximal r-Radius Subgraph

Maximal r-Radius Subgraph

Outline Semantic relations among terms  term association graph (TAG) Close relations  maximal r-radius subgraph Compactness  group Steiner problem Size+relevance  assembly Evaluation

Sub-snippet Generation Given a maximal r-radius subgraph Gi and a set of relevant keywords Qi = {q1;…;qg}, a sub-snippet Gsub is a connected subgraph of Gi satisfying qQi, vV(Gsub) such that qLblV(v). Compact sub-snippet

Sub-snippet Generation

Sub-snippet Generation

Outline Semantic relations among terms  term association graph (TAG) Close relations  maximal r-radius subgraph Compactness  group Steiner problem Size+relevance  assembly Evaluation

Snippet Generation Requirements Compactness Relevance Quality = *Compactness + (1-)*Relevance Snippet S max(Quality(GS)) size(GS)<=restriction Greedy method maximal marginal increase

Snippet Generation

Evaluation Feasibility 4,522 ontologies two 4-core Xeon E7400 (2.4G) and 24GB memory

Evaluation Effectiveness Competitors Participants Experimental Design Term set (Term.S, Term.W) Sentence set (Sent, Sent+Q) Term Association (TA+C, TA) Participants 30 volunteers Experimental Design 10 topics from ODP Questionnaire

Evaluation

Any questions welcome