BSc CS Sem 6 2022 2023 2023 INFORMATION RETRIEVAL Question Paper - Mumbai University | munotes

Questions asked in this paper

• 2) Figures to the right indicate marks

1. Q3 Illustrations, in-depth answers and diagrams will be appreciated
2. Q4 Mixing of sub-questions is not allowed
3. Q1 Attempt All
   • (a) Select the correct alternative from the options given: (10M)
   • (i) Information retrieval is querying of textual data
   • (a) Structured (b) Unstructured
   • (ii) is what fraction of the relevant documents in the collection were returned by the system
   • (c) Precision (d) Recall
   • (iii) Ina , the dictionary contains all k-grams_ that occur in any term in the vocabulary
   • (iv) Which of the following is a technique for context sensitive spelling
   • (a) The Jaccard Coefficient (b) Soundex algorithms
   • (v) takes a set of data and converts it into another set of data, where individual elements are broken down into tuples (key/value pairs)
   • (a) Map (b) Reduce
   • (vi) in Information retrieval are short fragments of text extracted from the document content or its metadata
   • (a) snippets (b) question answering
   • (c) long document (d) metadata of document
   • (vii) problem means that there is a need to be enough other users already in the system to find a match
   • (d) Cold start
   • (viii) approaches are commonly used for data collections with complex structures that mainly contain nontext data
   • (ix) The standard for accessing and processing XML documents is the XML
   • (x) refers to a huge database of internet resources such as web
   • (b) Fill in the blanks by selecting from the pool of options: (5M)
   • (i) When we replace a character of a string by another character, it is called as
   • (ii) A good page for a topic links to many authority pages for that
   • (iii) forms a directed edge from one node to another node in a web
   • (iv) XML stands for
   • (v) is the algebraic model for representing text documents as vectors of identifiers
4. Q2 Attempt the following (Any THREE) (15M)
   • (a) Explain inverted index used in IR with the help of an example
   • (b) Explain the following terms
   • i) Corpus
   • ii) Precision
   • iii) Recall
   • v) Token
   • (c) Draw the term document incidence matrix for the following document collection and answer the given queries Doc 2 home sales rise in july Doc 3 increase in home sales in july
   • i) Home and sales and july
   • ii) Rise and sales not increase
   • (d) Explain the search process using Binary tree
   • (e) Explain the SOUNDEX algorithm used in Phonetic correction
   • (f) What is spelling correction? State and explain its different forms
5. Q3 Attempt the following (Any THREE) (15M)
   • (a) Explain hubs and authorities in detail
   • (b) How page rank algorithm is used for ranking webpages?
   • (c) Explain how term frequency and inverse document frequency can be used in ranking web pages?
   • (d) Explain the HDFS architecture
   • (e) State the advantages and disadvantages of personalized search
   • (f) What is snippet? Explain its importance in information retrieval
6. Q4 Attempt the following (Any THREE) 15 marks
   • (a) Explain the following terms in SPAM
   • i) Content hiding
   • ii) Cloaking
   • iii) Redirection
   • v) Term spamming
   • (b) What is user query? State and explain the different types of queries entered by the user
   • (c) What is Web search architecture? Explain its components
   • (d) How Vector space model is used for information retrieval?
   • (e) Explain the Data Centric XML retrieval with the help of examples
   • (f) What is XML retrieval system? State and explain the challenges of XML
7. Q5 Attempt the following (Any FIVE) 15 marks
   • (a) State the challenges in information retrieval
   • (b) Compute the Edit distance to convert CATS to FATS
   • (c) Explain invisible web
   • (d) What is the need of question answering system?
   • (e) What is Collaborative filtering?
   • (f) Explain the indexing process in search engine
   • (g) Explain the following:
   • i) Web graph
   • (h) What is black hat SEO?

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