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Event-Dataset: Temporal information retrieval and text classification dataset.

Shafiq Ur Rehman Khan1, Muhammad Arshad Islam1

  • 1Capital University of Science and Technology, Islamabad, Pakistan.

Data in Brief
|June 14, 2019
PubMed
Summary
This summary is machine-generated.

Researchers developed the Event-dataset, a new benchmark for evaluating focus time assessment in Temporal Information Retrieval (TIR). This dataset aids in assessing temporal relevance for user information needs.

Keywords:
Focus time assessmentInformation retrievalTemporalText classification

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Area of Science:

  • Information Retrieval
  • Computer Science
  • Data Science

Background:

  • Temporal Information Retrieval (TIR) is gaining prominence, utilizing temporal dynamics alongside textual relevance.
  • Focus time, the time a document refers to, is a crucial temporal aspect in TIR.
  • Existing benchmarks lack comprehensive evaluation capabilities for focus time assessment strategies.

Purpose of the Study:

  • To introduce a novel benchmark dataset for evaluating focus time assessment strategies in TIR.
  • To provide a standardized resource for researchers in the information retrieval community.
  • To facilitate the evaluation of temporal relevance in information retrieval systems.

Main Methods:

  • A new dataset, Event-dataset, was created, comprising 35 queries representing popular events.
  • Each query is associated with a set of news articles, categorized into relevant and non-relevant documents.
  • A user-study involving postgraduate students was conducted for manual annotation of articles.

Main Results:

  • The Event-dataset provides a structured collection of queries and annotated news articles.
  • It enables the evaluation of document relevance based on their temporal focus.
  • The dataset serves as a benchmark for focus time assessment and general information retrieval methods.

Conclusions:

  • The Event-dataset addresses the need for a standard benchmark in Temporal Information Retrieval.
  • It empowers researchers to rigorously evaluate focus time assessment techniques.
  • This resource is expected to advance the field of temporal information retrieval.