Presentation is loading. Please wait.

Presentation is loading. Please wait.

INFORMATION RETRIEVAL VECTOR SPACE MODEL IN-DEPTH PART 2 Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics.

Similar presentations


Presentation on theme: "INFORMATION RETRIEVAL VECTOR SPACE MODEL IN-DEPTH PART 2 Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics."— Presentation transcript:

1

2 INFORMATION RETRIEVAL VECTOR SPACE MODEL IN-DEPTH PART 2 Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics

3 Inverse Document Frequency (IDF) 2

4 Inverse Document Frequency 3

5 4

6 Document/Term Matrix 5

7 Weight Factor Computation 6

8 VSM Pros and Cons 7  Benefits  Documents can be ordered by importance  Threshold display limits are easy to honor  Documents similar to the query retrieved early can be used for relevance feedback  Drawbacks  Orthogonal terms assumption is false  Some vector operations have no theoretical justification

9 References 8 Sources: Introduction to Information Retrieval by Christopher Manning, Prabhakar Raghavan and Hinrich Schütze, The Cambridge University Press Automatic Text Processing Gerard Salton, Addison-Wesley Publishing.

10 The end of the second in-depth description of the vector space model slide show has come. End of the Slides 9


Download ppt "INFORMATION RETRIEVAL VECTOR SPACE MODEL IN-DEPTH PART 2 Thomas Tiahrt, MA, PhD CSC492 – Advanced Text Analytics."

Similar presentations


Ads by Google