The Nature of Novelty Detection
Le Zhao, Min Zhang, Shaoping Ma

TL;DR
This paper investigates the fundamental nature of sentence-level novelty detection, revealing it as a combination of partial and complete overlap relations, and proposes new methods and evaluation metrics based on this understanding.
Contribution
It formalizes novelty detection as a combination of partial and complete overlaps, introduces the selected pool method, and proposes new evaluation measures aligned with this understanding.
Findings
Selected pool method outperforms existing methods
Novel evaluation metrics improve assessment accuracy
Task understanding influences evaluation approaches
Abstract
Sentence level novelty detection aims at reducing redundant sentences from a sentence list. In the task, sentences appearing later in the list with no new meanings are eliminated. Aiming at a better accuracy for detecting redundancy, this paper reveals the nature of the novelty detection task currently overlooked by the Novelty community Novelty as a combination of the partial overlap (PO, two sentences sharing common facts) and complete overlap (CO, the first sentence covers all the facts of the second sentence) relations. By formalizing novelty detection as a combination of the two relations between sentences, new viewpoints toward techniques dealing with Novelty are proposed. Among the methods discussed, the similarity, overlap, pool and language modeling approaches are commonly used. Furthermore, a novel approach, selected pool method is provided, which is immediate following…
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Taxonomy
TopicsTopic Modeling · Advanced Text Analysis Techniques · Natural Language Processing Techniques
