Relevance Feedback
- In the section 9.1, the authors wrote the following: “RF can also be effective in tracking a user’s evolving information need”. I am not so sure of this, because if the user understands better her information need, will probably reformulate her query instead of waiting for the system to recalculate a result set.
Foundations of the Rocchio Algorithm
- I don’t understand how the formula (9.2)
is derived from the formula 6.10 of vector similarity.
The Rocchio Algorithm
- The book states that Relevance Feedback has shown to be useful for increasing recall in situations where it is important, and one of the reasons is because the technique expands the query. Is this always true? When I expand the query and I do a Boolean match of the query terms with AND, adding more terms can increase precision but not necessarily recall. Now, I know that in this case this is a VSM and not a Boolean one, but it is always true that adding terms to query the recall is increased?
- Besides, I don’t understand clearly the IDE DEC-HI concept.
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