Improving VIVO search through semantic ranking.

Improving VIVO search results through Semantic Ranking. Anup Sawant Deepak Konidena

VIVO Search till Release 1.2.1 ,[object Object],[object Object],[object Object],[object Object],[object Object]

Adding knowledge from semantic relationships ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Lucene field for an Individual. And here's why

Intermediate nodes were overlooked. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

How does the semantic graph look like with the presence of context nodes?

VIVO Search in 1.3 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Enriching Individuals with Semantic Relations. ,[object Object],[object Object],[object Object]

Influence of PageRank ,[object Object],[object Object],[object Object]

Some parameters based on PageRank ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Search Index Architecture: Enriching with Semantic Relations. Overall connectivity of an Individual (ß) Apache Solr Relevant Documents. Dismax Query Handler. Indexing Phase Sparql Proper Boosts Searching Phase Multithreaded.

Real-time Indexing: Enriching with Semantic Relations. Overall connectivity of an Individual (ß) Apache Solr Relevant Documents. Dismax Query Handler. Indexing Phase Sparql Proper Boosts Searching Phase ADD/EDIT/DELETE of an Individual or its properties. The changes occur in real time and propagate beyond intermediate nodes. Multithreaded.

Cluster Analysis of Search Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Query Distance from Mean vector of Release 1.2.1 Distance from Mean vector of Release 1.3 Scripps 0.27286328362357193 0.004277746256068157 Paulson James 0.009907336493786136 0.004650133621323327 Genome Sequencing 9.185463752863598E-4 8.154498815206635E-4 Kenny Paul 0.007610235640599918 0.003984303949283425

Understanding how it happens .. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],name location description name research name articles name location Bla bla bla ….

Understanding how it happens .. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],R1 R2 R3 .. .. .. .. 6 1 Q 1 0 0 1 4 0 1 1 0 1 4 0 1 1 0 1 1 1 1 0 0 0 - - - - - - - - - - - - - - - -

Understanding how it happens .. institute cornell loring V1 V2 θ Euclidean distance Cosine distance

Understanding how it happens .. institute cornell loring V2 θ V1 Euclidean distance increases, Cosine distance remains the same

Query vector distance from Cluster Mean vectors

Precision and Recall Total Relevant Total Retrieved Precision = X / (Total Retrieved) Recall = X / (Total Relevant) X

Precision-Recall graphs based on User Analysis.

Cluster Analysis for Relevance

Precision-Recall graphs based on Cluster Analysis

Query vector distance from individual search result vectors

Experiments : SOLR ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Experiments : SOLR ( cont. ) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Experiments : Ontology provides a good base for Factoid Questioning. ,[object Object],[object Object],[object Object],[object Object]

Experiments : Ontology provides a good base for Factoid Questioning. ( cont. ) ,[object Object],[object Object],Stanford Lexparser Kmeans/SVM Search Query SPARQL Query Corpora Question type Terms

Summary ,[object Object],[object Object],[object Object],[object Object]

Improving VIVO search through semantic ranking.

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