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  1. Proceedings of the 20th Australasian Document Computing Symposium (ADCS '15)
  2. INST: An Adaptive Metric for Information Retrieval Evaluation
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Collision Resolution in Hash Tables for Vocabulary Accumulation During Parallel Indexing
Improving Throughput of a Pipeline Model Indexer
CQADupStack: A Benchmark Data Set for Community Question-Answering Research
Efficient Location-Aware Web Search
INST: An Adaptive Metric for Information Retrieval Evaluation
The effect of assessor coverage and assessor accuracy on rank aggregation precision
A Study on the Use of Word Embeddings and PageRank for Vietnamese Text Summarization
Towards Searching Amongst Tables
How Well Sentence Embeddings Capture Meaning
Data Fusion for Japanese Term and Character N-gram Search
Text segmentation and Chinese site search
Integrating and Evaluating Neural Word Embeddings in Information Retrieval

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INST: An Adaptive Metric for Information Retrieval Evaluation

Content Provider ACM Digital Library
Author Thomas, Paul Moffat, Alistair Scholer, Falk Bailey, Peter
Abstract A large number of metrics have been proposed to measure the effectiveness of information retrieval systems. Here we provide a detailed explanation of one recent proposal, INST, articulate the various properties that it embodies, and describe a number of pragmatic issues that need to be taken in to account when writing an implementation. The result is a specification for a program inst_eval for use in TREC-style IR experimentation.
Starting Page 1
Ending Page 4
Page Count 4
File Format PDF
ISBN 9781450340403
DOI 10.1145/2838931.2838938
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2015-12-08
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Relevance measures Test collections User behavior
Content Type Text
Resource Type Article
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