1. A Vector Space Model for Automatic Indexing
G. Salton, A. Wong and C. S. Yang
Enhanced Vector Space Models for Content-based Recommender Systems
Cataldo Musto
Presenter
Sawood Alam

2. A Vector Space Model for Automatic Indexing
G. Salton, A. Wong and C. S. Yang
Cornell University

3. Introduction
In document retrieval, best indexing space is where each entity lies far away from others
Density of the object space becomes a measure of indexing system
Retrieval performance correlate inversely with space density

4. Document Space
Di = (di1, di2, di3, …, dij)

5. Document Space (cont.)

6. Document Space (cont.)

7. Indexing Performance vs. Space Density

8. Cluster Density vs. Indexing Performance

9. Discrimination Value Model

10. Discrimination Value Model (cont.)

11. Discrimination Value Model Summary

12. Average Recall vs. Precision

13. Summary Recall vs. Precision

14. Enhanced Vector Space Models for Content-based Recommender Systems
Cataldo Musto
Dept. of Computer Science
University of Bari, Italy

15. Introduction
Vector Space Models (VSM) in Information Retrieval is an established practice
Investigate the impact of vector space models in Information Filtering
Recommender system

16. Problems of VSM High dimensionality
Becoming more serious due to emerging social apps and micro-blogging, generating lots of web content and new vocabulary
Inability to manage document semantics
Order of the term occurrence in the document

17. Components Context vector for each term Values in {-1, 0, 1}
Vector Space representation of a term (t)
Vector Space representation of a document (d)
Vector Space representation of a user profile (pu)

18. Indexing Technique Random Indexing-based model
Weighted Random Indexing-based model
Semantic Vector-based model
Weighted Semantic Vector-based model

19. Experimental Evaluation

20. Conclusions
First prototype with naive weighting scheme is comparable to other content based filtering techniques like Bayesian classifier
Other complex weighting schemes should perform better
User profiles may be studied based on Linked Data rather than keyword based user profiles