# CS726 – Information Retrieval Techniques Viva Preparation

 Question 01 What is Information Retrieval (IR)? Answer: IR is the techniques of storing and recovering and often disseminating recorded data especially through the use of a computerized system

 Question 02 What is precision Information Retrieval (IR)? Answer: Precision (P) is the fraction of retrieved documents PRECISION that are relevant. This is the percentage of retrieved documents that are in fact relevant to the query.Precision = Number of relevant document retrieved / Total number of documents retrieved

 Question 03 What is recall Information Retrieval (IR)? Answer: Recall (R) is the fraction of relevant documents that are retrieved. This is the percentage of documents that are relevant to the query and were in fact retrieved.Recall = Number of relevant documents retrieved / Total number of relevant documents

 Question 04 What are Models used in Information Retrieval (IR)? Answer: Boolean Model, Vector Model, Probabilistic Model

 Question 05 What is Boolean Model used in Information Retrieval (IR)? Answer: The Boolean retrieval model is a model for information retrieval in which we can pose any query which is in the form of a Boolean expression of terms, that is, in which terms are combined with the operators and, or, and not. The model views each document as just a set of words.

 Question 06 :      How we get relevant document in Information Retrieval (IR)? Answer: By using Precision and Recall method.

 Question 07        What are Information Retrieval (IR) ingredients? Answer:•      Documents representation•      Query formulation•      Query processing

 Question 08           How we measure relevant document in IR? Answer: The two most frequent and basic measures for information retrieval effectiveness are precision and recall. By using these measures we can measure relevant document.

 Question 9    What is TF-IDF? Answer:  In information retrieval, tf–idf, short for term frequency–inverse document frequency, is a numerical statistic that is intended to reflect how important a word is to a document in a collection or corpus. It is often used as a weighting factor in information retrieval, text mining, and user modeling.

 Question 10  What is Probabilistic Model? Answer: The probabilistic model computes the similarity coefficient between queries and documents as the probability that a document will be relevant to a query.

 Question 11      What is Ranking Function? Answer: A function that assigns scores to documents with regard to a given query.

 Question 12  What is Query Vector in IR? Answer:  Presenting queries in the term of vector space is called Query vector. Query vector is typically treated as a document and also tf-idf weighted.

 Question 13   What is Similarity Measure? Answer: A similarity measure is a function that computes the degree of similarity between two vectors.