Webpage retrieval based on query by example for think tank construction

Geng, Qingbo; Chuai, Ziang; Jin, Jian

doi:10.1016/j.ipm.2021.102767

Cited by 4 publications

(1 citation statement)

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“…Keywords and keyphrases are some of the most important tools in information technologies e.g., information extraction (IE) and information retrieval (IR). The information that keywords and keyphrases possess is substantial; they provide the building-blocks in searching and mining many different fields, including the industrial, legal, and academic fields [1][2][3][4][5][6]. Therefore, the rapid growth of automatic extraction and analysis of keywords and keyphrases is inevitable.…”

Section: Introductionmentioning

confidence: 99%

Extraction of time-related expressions using text mining with application to Hebrew

Mughaz,

HaCohen-Kerner,

Gabbay

2024

PLoS ONE

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In this research, we extract time-related expressions from a rabbinic text in a semi-automatic manner. These expressions usually appear next to rabbinic references (name / nickname / acronym / book-name). The first step toward our goal is to find all the expressions near references in the corpus. However, not all of the phrases around the references are time-related expressions. Therefore, these phrases are initially considered to be potential time-related expressions. To extract the time-related expressions, we formulate two new statistical functions, and we use screening and heuristic methods. We tested these statistical functions, grammatical screenings, and heuristic methods on a corpus containing responsa documents. In this corpus, many rabbinic citations are known and marked. The statistical functions and the screening methods filtered the potential time-related expressions and reduced 99.88% of the initial expressions (from 484,681 to 575).

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