The document compares and contrasts concept-based search using SySearch versus traditional keyword search. SySearch uses concepts extracted from documents and queries to understand information needs better than keyword matching alone. It ranks results by estimating the probability of relevance using a Bayesian approach rather than binary keyword matching. This allows it to better support natural language queries and retrieve more relevant results.

1. Concept Based Search SySearch vs. Traditional Search Simplified Version for External Yu Wang, Engineering Manager

9. Example: Relevance Ranking (1) A user wants to find an article which introduces both apple and orange. He inputs query string {Apple, Orange} and the system found 2 match documents. Both documents contain both query terms, while in D1 Apple appears 3 times Orange and in D2 Apple appears equally to Orange in occurrence. Is D1 or D2 more relevant to user need? Query Terms {Apple, Orange} Apple Orange Relevance Ranking Search Server Document Server Apple… Orange… Apple… Apple… Apple… Orange… Apple Orange… D1 D2 D1 Apple: Orange=3:1 D2 Apple: Orange=1:1 D1>D2? D2>D1?

12. SySearch Functional Architecture SySearch Web GUI/API System Administration Security/CSI Event Framework Log Management Category Document Group Meta-Data Scheduler Query Bayesian Engine Augmentation Expansion FS DB EM Document Import Document Filtering Content Add-on Meta-data Parser Text Processing Term Lexicon Index MPF Index Meta-data Index Term Index FS MPF Index Meta-data Index Term Index DB

15. Distributed SySearch Deployment

16. Q&A