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https://doi.org/10.3115/111893...
Article . 2003 . Peer-reviewed
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Temporal ranking for fresh information retrieval

Authors: Nobuyoshi Sato; Minoru Uehara; Yoshifumi Sakai;

Temporal ranking for fresh information retrieval

Abstract

In business, the retrieval of up-to-date, or fresh, information is very important. It is difficult for conventional search engines based on a centralized architecture to retrieve fresh information, because they take a long time to collect documents via Web robots. In contrast to a centralized architecture, a search engine based on a distributed architecture does not need to collect documents, because each site makes an index independently. As a result, distributed search engines can be used to retrieve fresh information. However, fast indexing alone is not enough to retrieve fresh information, as support for temporal information based retrieval is also required. In this paper, we describe temporal information retrieval in distributed search engines. In particular, we propose an implementation of temporal ranking.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Average
Top 10%
Average
bronze