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Ng, Kwong Bor; Kantor, Paul B.; Strzalkowski, Tomek; Wacholder, Nina; Tang, Rong; Bai, Bing; Rittman, Robert; Song, Peng; Sun, Ying

doi:10.1002/asi.v57:9

Cited by 21 publications

(4 citation statements)

References 209 publications

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“…It combines both the number of papers and their quality (impact, or citations to these papers) [23]. The h-index is recognized by the ISI Web of Science by Thomson Reuters or Scopus by Elsevier, as an important indicator for assessing research impact [21,24,25].…”

Section: H-indexmentioning

confidence: 99%

“…One might say that the h-index favors the researchers that have many cited publications. A scientist with very few highly cited papers or a scientist with many lowly cited papers will have a weak h-index [24], [26]. To address this issue, Hirsch presented the "m parameter" in [21] that divides h by the scientific age of a scientist (number of years since the author's first publication) to attenuate this problem.…”

Section: H-indexmentioning

confidence: 99%

See 1 more Smart Citation

Ranking MEDLINE documents

2014

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Background: BioTextRetriever is a Web-based search tool for retrieving relevant literature in Molecular Biology and related domains from MEDLINE. The core of BioTextRetriever is the dynamic construction of a classifier capable of selecting relevant papers among the whole MEDLINE bibliographic database. "Relevant" papers, in this context, means papers related to a set of DNA or protein sequences provided as input to the tool by the user. Methods: Since the number of retrieved papers may be very large, BioTextRetriever uses a novel ranking algorithm to retrieve the most relevant papers first. We have developed a new methodology that enables the automation of the assessment process based on a multi-criteria ranking function. This function combines six factors: MeSH terms, paper's number of citations, author's h-index, journals impact factor, author number of publications and journal similarity function. Results:The best results highlight the number of citations and the h-index factors. Conclusions:We have developed and a multi-criteria ranking function, that contemplates six factors, and that seems appropriate to retrieve relevant papers out of a huge repository such as MEDLINE.

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Section: H-indexmentioning

confidence: 99%

Section: H-indexmentioning

confidence: 99%

Ranking MEDLINE documents

2014

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“…An example of worthiness detection is the report written by Ng et al [133] on an investigation of document worthiness within a newspaper and newswire domain. The qualities that are investigated in the paper are: accuracy; source reliability; objectivity; depth; author credibility; readability; verbosity/conciseness; grammatical correctness; one-sided/multiviews, and are viewed as complementary to relevance.…”

Section: Detecting Worthinessmentioning

confidence: 99%

Contextual Search: A Computational Framework

Melucci

2012

FNT in Information Retrieval

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“…Efforts in understanding document worthiness using content variables have mainly been conducted through user studies, since human experts are able to assess document qualities and contribute to building training sets. An example of worthiness detection is the report written by Ng et al [133] on an investigation of document worthiness within a newspaper and newswire domain. The qualities that are investigated in the paper are: accuracy; source reliability; objectivity; depth; author credibility; readability; verbosity/conciseness; grammatical correctness; one-sided/multiviews, and are viewed as complementary to relevance.…”

Section: Detecting Worthinessmentioning

confidence: 99%

Contextual Search: A Computational Framework

Melucci¹

2012

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The growing availability of data in electronic form, the expansion of the World Wide Web (WWW) and the accessibility of computational methods for large-scale data processing have allowed researchers in Information Retrieval (IR) to design systems which can effectively and efficiently constrain search within the boundaries given by context, thus transforming classical search into contextual search. Because of the constraints imposed by context, contextual search better focuses on the user's relevance and improves retrieval performance, since the out-of-context aspects of the search carried out by users that are likely linked to irrelevant documents are left apart.This survey introduces contextual search within a computational framework based on contextual variables, contextual factors and statistical models. The framework adopted in this survey considers Query IntentQuery: from Latin quaerere, "ask, seek." Intent: from Latin intendere ("intend," "direct"), from in-"toward" + tendere "stretch," "tend." Oxford Dictionary

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Cited by 21 publications

References 209 publications

Ranking MEDLINE documents

Ranking MEDLINE documents

Contextual Search: A Computational Framework

Contextual Search: A Computational Framework

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