Information Retrieval
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1 Information Retrieval Venkatesh Vinayakarao Term: Aug Dec, 2018 Indian Institute of Information Technology, Sri City Characteristic vectors representing code are often high dimensional, e.g., there are more than two hundreds different syntactic element types in Java ASTs.. Lee et al. From their paper, Instant Code Clone Search. Love Tarun Venkatesh Vinayakarao (Vv)
2 Relevance Feedback
3 How to improve relevance? Relevance Feedback And Query Expansion
4 The Problem of Synonymy What result do you expect for a query, plane? What if plane appears in this query, plane from Delhi to Goa? So many synonyms which will work for web search Flight Aircraft Airplane Aeroplane By Air Fly Flgt Arcrft
5 How to ensure good results? Automatic Query Refinement Local Global Use the query or the results for reformulating the query We will study: Relevance Feedback Pseudorelevance Indirect Relevance Feedback Do not use the query or the results for reformulating the query. Eg: Use Thesaurus. Do Spelling Correction.
6 Relevance Feedback + Result 1 + Result 2 - Result 3 Query Results Search System Reformulated Query Results Search System
7 An Example Image source:
8 Interesting Characteristics Indexed content is unknown to the user. Information Need changes after looking at the results. User visits youtube to listen to a specific set of songs. After the first song, he changes his mind and listens to something else!
9 A Recap of Vector Space Models Image Source:
10 Rocchio Algorithm for Relevance Feedback Image Source:
11 Moving the Centroid! Modify the query (and therefore, the query vector from q0 to qm): D r = Set of known relevant documents D nr = Set of known nonrelevant documents q o = Initial query vector q m = Modified query vector
12 Rocchio relevance feedback - Example Given: Initial query = cheap CDs cheap DVDs extremely cheap CDs. d 1 = CDs cheap software cheap CDs is judged as relevant. d 2 = cheap thrills DVDs is judged as nonrelevant What would the revised query vector be after relevance feedback? Let us solve this together Assume that we are using direct term frequency (with no scaling and no document frequency). There is no need to length-normalize vectors. Assume α = 1, β = 0.75, γ = 0.25.
13 Representing Initial Query in Vector Space Initial query = cheap CDs cheap DVDs extremely cheap CDs. cheap CDs DVDs extremely software thrills q
14 Rocchio relevance feedback - Example Quiz: Can you complete the following table? q 0 = cheap CDs cheap DVDs extremely cheap CDs. d 1 = CDs cheap software cheap CDs. d 2 = cheap thrills DVDs. cheap CDs DVDs extremely software thrills q d 1 d 2
15 Rocchio relevance feedback - Example Quiz: Can you complete the following table? q 0 = cheap CDs cheap DVDs extremely cheap CDs. d 1 = CDs cheap software cheap CDs. d 2 = cheap thrills DVDs. cheap CDs DVDs extremely software thrills q d d
16 Moving Vectors Move (2,2) to (5,2) by adding 3 to x. 56
17 Rocchio relevance feedback - Example Quiz: How to calculate the modified query vector, q m? d 1 is judged as relevant. d 2 is judged as non-relevant. Assume α = 1, β = 0.75, γ = cheap CDs DVDs extremely software thrills q d d q m
18 Rocchio relevance feedback - Example Quiz: How to calculate the modified query vector, q m? d 1 is judged as relevant. d 2 is judged as nonrelevant. Assume α = 1, β = 0.75, γ = cheap CDs DVDs extremely software thrills q d d Negative weight does not make sense. So, leave them as zero. q m = q *d *d 2 q m
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