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Advances in Information Retrieval Theory

Overview of attention for book
Cover of 'Advances in Information Retrieval Theory'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Is There Something Quantum-Like about the Human Mental Lexicon?
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    Chapter 2 Probably Approximately Correct Search
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    Chapter 3 PageRank: Splitting Homogeneous Singular Linear Systems of Index One
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    Chapter 4 Training Data Cleaning for Text Classification
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    Chapter 5 Semi-parametric and Non-parametric Term Weighting for Information Retrieval
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    Chapter 6 Bridging Language Modeling and Divergence from Randomness Models: A Log-Logistic Model for IR
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    Chapter 7 Ordinal Regression Based Model for Personalized Information Retrieval
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    Chapter 8 Navigating in the Dark: Modeling Uncertainty in Ad Hoc Retrieval Using Multiple Relevance Models
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    Chapter 9 A Belief Model of Query Difficulty That Uses Subjective Logic
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    Chapter 10 “A term is known by the company it keeps”: On Selecting a Good Expansion Set in Pseudo-Relevance Feedback
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    Chapter 11 An Effective Approach to Verbose Queries Using a Limited Dependencies Language Model
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    Chapter 12 Time-Sensitive Language Modelling for Online Term Recurrence Prediction
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    Chapter 13 Score Distributions in Information Retrieval
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    Chapter 14 Modeling the Score Distributions of Relevant and Non-relevant Documents
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    Chapter 15 Modeling Expected Utility of Multi-session Information Distillation
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    Chapter 16 Specificity Aboutness in XML Retrieval
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    Chapter 17 An Effectiveness Measure for Ambiguous and Underspecified Queries
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    Chapter 18 An Analysis of NP-Completeness in Novelty and Diversity Ranking
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    Chapter 19 From “Identical” to “Similar”: Fusing Retrieved Lists Based on Inter-document Similarities
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    Chapter 20 A Quantum-Based Model for Interactive Information Retrieval
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    Chapter 21 The Quantum Probability Ranking Principle for Information Retrieval
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    Chapter 22 Written Texts as Statistical Mechanical Problem
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    Chapter 23 What Happened to Content-Based Information Filtering?
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    Chapter 24 Prior Information and the Determination of Event Spaces in Probabilistic Information Retrieval Models
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    Chapter 25 Robust Word Similarity Estimation Using Perturbation Kernels
  27. Altmetric Badge
    Chapter 26 Possibilistic Similarity Estimation and Visualization
  28. Altmetric Badge
    Chapter 27 A New Measure of the Cluster Hypothesis
  29. Altmetric Badge
    Chapter 28 Explaining User Performance in Information Retrieval: Challenges to IR Evaluation
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    Chapter 29 A Four-Factor User Interaction Model for Content-Based Image Retrieval
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    Chapter 30 Predicting Query Performance by Query-Drift Estimation
  32. Altmetric Badge
    Chapter 31 What’s in a Link? From Document Importance to Topical Relevance
  33. Altmetric Badge
    Chapter 32 Avoiding Bias in Text Clustering Using Constrained K-means and May-Not-Links
  34. Altmetric Badge
    Chapter 33 Optimizing WebPage Interest
  35. Altmetric Badge
    Chapter 34 The “Beautiful” in Information
  36. Altmetric Badge
    Chapter 35 IR Evaluation without a Common Set of Topics
  37. Altmetric Badge
    Chapter 36 An Ad Hoc Information Retrieval Perspective on PLSI through Language Model Identification
  38. Altmetric Badge
    Chapter 37 Less Is More: Maximal Marginal Relevance as a Summarisation Feature
  39. Altmetric Badge
    Chapter 38 On the Notion of “An Information Need”
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    Chapter 39 A Logical Inference Approach to Query Expansion with Social Tags
  41. Altmetric Badge
    Chapter 40 Evaluating Mobile Proactive Context-Aware Retrieval: An Incremental Benchmark
  42. Altmetric Badge
    Chapter 41 Predicting the Usefulness of Collection Enrichment for Enterprise Search
  43. Altmetric Badge
    Chapter 42 Ranking List Dispersion as a Query Performance Predictor
  44. Altmetric Badge
    Chapter 43 Semi-subsumed Events: A Probabilistic Semantics of the BM25 Term Frequency Quantification
  45. Altmetric Badge
    Chapter 44 Batch-Mode Computational Advertising Based on Modern Portfolio Theory
Overall attention for this book and its chapters
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Mentioned by

patent
1 patent

Readers on

mendeley
38 Mendeley
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Title
Advances in Information Retrieval Theory
Published by
ADS, August 2009
DOI 10.1007/978-3-642-04417-5
ISBNs
978-3-64-204416-8, 978-3-64-204417-5
Editors

Leif Azzopardi, Gabriella Kazai, Stephen Robertson, Stefan Rüger, Milad Shokouhi, Dawei Song, Emine Yilmaz

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 3%
Unknown 37 97%
Readers by discipline Count As %
Computer Science 1 3%
Unknown 37 97%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 March 2022.
All research outputs
#7,687,335
of 23,390,392 outputs
Outputs from ADS
#9,457
of 38,006 outputs
Outputs of similar age
#32,958
of 92,738 outputs
Outputs of similar age from ADS
#119
of 413 outputs
Altmetric has tracked 23,390,392 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 38,006 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 92,738 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 413 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.