Information Retrieval c1-c4
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Questions and Answers

What is the primary focus of information retrieval?

  • Storing large amounts of data efficiently
  • Finding unstructured material to meet information needs (correct)
  • Finding structured data in databases
  • Analyzing statistical data from government institutions

    • Which of the following represents a major advancement in information retrieval since the year 2000?

  • Link analysis and ranking algorithms (correct)
  • Boolean retrieval methods
  • Basic document retrieval systems
  • Use of index cards for organization

    • How does information retrieval differ from traditional database systems?

  • IR uses probabilistic models; databases use deterministic models. (correct)
  • IR requires exact matches; databases tolerate errors.
  • IR focuses on fully structured queries; databases do not.
  • IR uses SQL for querying; databases do not.

    • What type of data is typically involved in information retrieval?

    <p>Unstructured data such as text documents (A)</p> Signup and view all the answers

    In the context of information retrieval, what does the term 'sparse matrix' refer to?

    <p>A representation with many zeros and few ones (C)</p> Signup and view all the answers

    Which statement accurately describes a characteristic of information retrieval systems?

    <p>They allow partial matches despite incomplete queries. (A)</p> Signup and view all the answers

    What technological advancement in information retrieval is associated with semantic web technologies since 2010?

    <p>Development of user recommendation systems (C)</p> Signup and view all the answers

    Which of the following best describes Boolean retrieval?

    <p>It involves the use of logical operators like AND and OR. (C)</p> Signup and view all the answers

    What is an essential function of multimedia information retrieval systems?

    <p>They analyze audio and video content for information extraction. (D)</p> Signup and view all the answers

    What does the process of 'categorization' in information retrieval aim to achieve?

    <p>To cluster similar documents together based on content (C)</p> Signup and view all the answers

    What is the purpose of creating an inverted index?

    <p>To maintain a list of document IDs where each word appears (B)</p> Signup and view all the answers

    What is normalization in the context of information retrieval?

    <p>To convert words into their base forms (C)</p> Signup and view all the answers

    In boolean retrieval, how should lists be processed for efficiency?

    <p>By beginning with the shortest posting list (C)</p> Signup and view all the answers

    What distinguishes a token from a type in information retrieval?

    <p>Tokens represent character sequences, while types are the class of those sequences (C)</p> Signup and view all the answers

    Why are bytes per token often smaller than bytes per term?

    <p>Shorter words are excluded from terms (C)</p> Signup and view all the answers

    What is the role of the Map phase in the retrieval process?

    <p>To create a word list with document IDs as values (A)</p> Signup and view all the answers

    What must be considered when sorting data stored on a disk or SSD?

    <p>Data cannot be accessed randomly (D)</p> Signup and view all the answers

    What does the Shuffle phase accomplish in the information retrieval process?

    <p>It collects identical words together (A)</p> Signup and view all the answers

    Which of the following correctly defines a term in an information retrieval system?

    <p>A class of tokens sharing the same character sequence (C)</p> Signup and view all the answers

    What is a key characteristic of boolean retrieval?

    <p>It strictly uses AND, OR, and NOT for precision (D)</p> Signup and view all the answers

    What is the Levenshtein distance mainly concerned with?

    <p>The minimum operations required to convert one string to another (D)</p> Signup and view all the answers

    Which method allows for measuring how closely two strings or words overlap?

    <p>Jaccard coefficient (B)</p> Signup and view all the answers

    What is a major disadvantage of using a hash table for word searching?

    <p>Possibility of collisions (A)</p> Signup and view all the answers

    What is the main purpose of the Reduce phase in document indexing?

    <p>To combine document IDs for unique words into a list (C)</p> Signup and view all the answers

    What distinguishes a B-tree from a binary tree?

    <p>B-trees can have multiple branches (C)</p> Signup and view all the answers

    What does the term 'biwords' refer to in the context of indexing?

    <p>Pairs of words combined for searching purposes (A)</p> Signup and view all the answers

    What happens when the vocabulary in a hash table grows?

    <p>The hash table must be rehashed (A)</p> Signup and view all the answers

    Which of the following is a characteristic of positional indexes?

    <p>They significantly increase memory usage (B)</p> Signup and view all the answers

    What is the effect of using stop words in indexing and queries?

    <p>They are removed to enhance indexing efficiency (C)</p> Signup and view all the answers

    What does 'phonetic similarity' refer to?

    <p>Sound-based resemblance of words (B)</p> Signup and view all the answers

    What is lemmatization in the context of natural language processing?

    <p>Reducing words to their base or root forms (B)</p> Signup and view all the answers

    In a binary tree search, what method is used to navigate through the tree?

    <p>Choosing between left or right paths based on letters (A)</p> Signup and view all the answers

    What does a skip list use to improve search performance?

    <p>Assigning probabilities to elements (A)</p> Signup and view all the answers

    Which algorithm is primarily used for stemming in the English language?

    <p>Porter's Algorithm (A)</p> Signup and view all the answers

    What is one of the main advantages of using a hash table for searching?

    <p>Computational complexity of O(1) for insert and search (A)</p> Signup and view all the answers

    How does context-sensitive spelling correction differ from isolated word correction?

    <p>It analyzes the context of surrounding words for better accuracy (B)</p> Signup and view all the answers

    Which of the following search methods does not perform well with expanding vocabularies?

    <p>Hash tables (A)</p> Signup and view all the answers

    What is the primary use of a positional index in document retrieval?

    <p>To help in the efficient lookup of documents by term position (C)</p> Signup and view all the answers

    What happens when a query includes common high-frequency words?

    <p>It reduces the relevance of the search results (A)</p> Signup and view all the answers

    What is the role of document correction in OCR documents?

    <p>To ensure that the representation of documents remains unchanged (C)</p> Signup and view all the answers

    Flashcards

    Information Retrieval (IR)

    Finding information (usually documents) from large collections (often stored on computers), typically unstructured (mostly text) to meet an information need.

    Boolean Retrieval

    A method for searching documents using logical operators like AND, OR, and NOT.

    Vector Space Model

    A method for representing documents and queries as vectors to calculate similarity based on the distance between vectors.

    Large Document Database Systems

    Systems that manage and store large collections of documents, typically run by organizations.

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    Sparse Matrix

    A matrix with many zero entries and relatively few non-zero entries.

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    Keyword Representation

    Using keywords as a way to help locate documents in a large collection.

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    Link Analysis & Ranking

    A method of evaluating and ordering relevance of webpages based on links between them.

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    IR vs. Databases

    IR typically deals with unstructured data and partial matches, while databases work with structured data and exact matches.

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    Multimedia IR

    Information Retrieval that includes multimedia data like images and video.

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    Latency

    The time taken to retrieve or access information.

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    Posting Lists

    A list of document IDs where a specific term appears.

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    Inverted Index

    A data structure that maps terms to document identifiers where they are present.

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    Normalization

    Converting words to their root form. Example: 'friends' becomes 'friend'.

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    Token

    A unit of text grouped for processing.

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    Type

    Group of tokens with same characters. e.g., 'friend', 'friends' are the same type

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    Term

    Normalized token included in the search system’s dictionary.

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    Bytes per token

    Storage space needed for a token in the index.

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    Map Phase

    Document words are listed with their IDs in document-term index.

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    Shuffle Phase

    Similar words are grouped together.

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    What is a positional index?

    A type of index that stores the positions of words within a document, allowing for more precise searching, like finding phrases.

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    What are biwords?

    Combining consecutive words into pairs, creating a new dictionary entry for each pair. For example, "information retrieval" becomes a single biword.

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    What is 'index blowup'?

    The dramatic increase in the size of an index when using techniques like biwords, especially when many common words are involved.

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    What is tokenization?

    Breaking down text into individual words or units.

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    What is compound splitting?

    Breaking long words into separate words, such as 'sicktekostenverzekeringsmaatschappij' becoming 'sick', 'kosten', 'verzekering', 'maatschappij'.

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    What is normalization?

    Converting text to a consistent format, typically lowercase, for easier comparison and indexing.

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    What are stop words?

    Common words that are often removed from text before indexing, such as 'the', 'of', and 'a'.

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    What is lemmatization?

    Reducing words to their base form or lemma, using a dictionary. For example, 'running', 'ran', and 'runs' all become 'run'.

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    What is stemming?

    Reducing words to their root or stem form, using rules. For example, 'automate' becomes 'automat'.

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    What is spelling correction?

    Identifying and correcting misspellings in text, either in documents or user queries.

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    Edit Distance

    The minimum number of insertions, deletions, or replacements needed to transform one string into another.

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    Weighted Edit Distance

    Similar to Edit Distance, but assigns different weights to different types of edit operations (insertions, deletions, replacements).

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    N-Gram Overlap

    A method for comparing strings based on the number of overlapping sequences of 'n' consecutive characters.

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    Jaccard Coefficient

    A measure of similarity between two sets, calculated as the ratio of the size of their intersection to the size of their union.

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    Phonetic Similarity

    Comparing how words sound, even if their spellings differ, to find close matches.

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    Hashtable (Hash Table)

    A data structure that uses a hash function to map keys to values and store them in an array, enabling fast access to data.

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    Computational Complexity O(1)

    Describes an algorithm whose execution time remains constant, regardless of the input size.

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    Binary Tree Search

    A search algorithm that traverses a binary tree, comparing the search key with the value at each node, and branching left or right accordingly.

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    B-tree

    A self-balancing tree data structure that allows efficient searching, insertion, and deletion of data, even for large amounts of data.

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    Skip List

    A probabilistic data structure that allows efficient search, insertion, and deletion operations by maintaining multiple levels of linked lists.

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    Study Notes

    Information Retrieval History

    • Information Retrieval (IR) was traditionally performed by archivists and librarians working for government agencies, military and secret services, academic institutions, statistical bureaus, religious figures, and cultural organizations.
    • IR involved locating documents relevant to information needs from large collections, often stored on computers.
    • Techniques originally involved physical libraries and archives.
    • Early methods were based on card catalogs, followed by automated systems like "Memex" using scanned documents (hyperlinks).
    • Boolean retrieval and vector space models followed.
    • The development of large document databases and their management by companies was a key milestone.
    • Web search and UseNet were introduced as significant advancements.

    IR Developments Post-2000

    • Significant developments include link analysis & ranking (Google), question answering, multimedia IR (image and video analysis), and cross-lingual IR.
    • Semantic web technologies (DBpedia) and advanced categorisations emerged.
    • IR differs from database systems in dealing with unstructured data, keyword sets (loose semantics), incomplete queries, requiring more tolerance for errors and the usage of probabilistic models.

    Information Retrieval Framework

    • The framework involves crawling, indexing, compressing indexes, link analysis, classification, and the implementation of a query processing engine.
    • Key processes are: indexing, query expansion, query execution, and relevance feedback.
    • Latency elements are critical: memory access, hard disk seeking, SSD (Solid State Disk) speed, network communications.

    Information Retrieval Framework Latency

    • L1 cache reference (0.5 ns)
    • Branch mispredict (5 ns)
    • L2 cache reference(7 ns)
    • Mutex lock/unlock (25 ns)
    • Main memory reference(100 ns)
    • Compressing 1KB with Zippy(3,000 ns = 3 µs)
    • Sending 2KB over a 1 Gbps network (20,000 ns = 20 µs)
    • SSD random read (150,000 ns = 150 µs)
    • Reading 1 MB sequentially from memory (250,000 ns = 0.25 ms)
    • Round trip within the same data centre(500,000 ns = 0.5 ms)
    • Reading 1 MB sequentially from SSD(1,000,000 ns = 1 ms)
    • Disk seek(10,000,000 ns = 10 ms)
    • Reading 1 MB sequentially from disk (20,000,000 ns = 20 ms)
    • Sending packet CA to Netherlands to CA (150,000,000 ns = 150 ms)

    Inverted Index Construction

    • The inverted index stores term/document ID pairs.
    • The dictionary stores terms and pointers to postings lists.
    • Posting lists contain document IDs and positions where terms appear.
    • Construction steps involve tokenizing text, normalizing tokens (e.g., lowercasing, stemming), and sorting terms alphabetically and by document IDs.
    • Sorting is done using a sort algorithm (e.g., Bubble Sort).

    Boolean Retrieval

    • A simple way to retrieve documents based on specific keywords.
    • It relies on logical operators such as AND, OR, and NOT to combine search terms.
    • Efficiency depends on the size of the index and number of matching documents.
    • Relevance is determined based on documents containing the search terms.

    Inverted Index

    • A data structure built to support fast retrieval of documents matching a query.
    • Dictionary: Mapping from terms to posting lists.
    • Inverted Lists: Pointers to documents where the corresponding words or phrases exist.

    Boolean Query Processing

    • Boolean retrieval processes queries by first performing a sequential lookup in the inverted lists.
    • This involves building postings lists from the dictionary, followed by merging lists using logical operators according to the query.

    Positional Indexing

    • This approach stores document position information in postings lists.
    • A benefit over traditional methods is improved context understanding in search results.
    • It aids in exact phrase searches, aiding in complex question answering capabilities.

    Distributed Indexing using MapReduce

    • Processes indexing across multiple machines for scalability.
    • Splitting documents into manageable subsets (e.g. 16-128MB) for parallel map tasks.
    • Generating key-value pairs (e.g., term, (docID, count/position)).
    • Grouping and sorting keys for efficient reduce operations.
    • Combining and sorting, resulting in inverted files.

    Wild Card Queries

    • Handling wildcard queries in IR systems involves using modified indexing and searching techniques to overcome the limitations of basic techniques.
    • This process generates permutation terms to achieve comprehensive matches in the inverted index, though this approach can considerably enlarge the size of the dictionary.

    Jaccard Coefficient

    • A measure of similarity between two sets.
    • It is given by dividing the intersection of the two sets by their union.
    • It can be utilized to measure the similarity between query terms and existing terms to identify the best possible matches.

    Phonetic Similarity

    • Measuring phonetic similarity involves comparing words based on their pronunciation.
    • It aids in handling spelling mistakes by retrieving relevant documents even with slight variations in letter/word order.
    • Context-sensitive corrections refine results by considering the surrounding words for correcting errors.

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    Description

    Explore the evolution of Information Retrieval (IR) from its early techniques involving physical libraries to the advancements post-2000. This quiz covers key milestones such as Boolean retrieval, web search, and modern multimedia IR methods. Test your knowledge on how information needs are met through evolving technologies.

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