27,242 research outputs found
Journal Name Extraction from Japanese Scientific News Articles
In Japanese scientific news articles, although the research results are
described clearly, the article's sources tend to be uncited. This makes it
difficult for readers to know the details of the research. In this paper, we
address the task of extracting journal names from Japanese scientific news
articles. We hypothesize that a journal name is likely to occur in a specific
context. To support the hypothesis, we construct a character-based method and
extract journal names using this method. This method only uses the left and
right context features of journal names. The results of the journal name
extractions suggest that the distribution hypothesis plays an important role in
identifying the journal names.Comment: The Asia-Pacific Signal and Information Processing Association Annual
Summit and Conference 2018 (APSIPA ASC 2018
Examining Scientific Writing Styles from the Perspective of Linguistic Complexity
Publishing articles in high-impact English journals is difficult for scholars
around the world, especially for non-native English-speaking scholars (NNESs),
most of whom struggle with proficiency in English. In order to uncover the
differences in English scientific writing between native English-speaking
scholars (NESs) and NNESs, we collected a large-scale data set containing more
than 150,000 full-text articles published in PLoS between 2006 and 2015. We
divided these articles into three groups according to the ethnic backgrounds of
the first and corresponding authors, obtained by Ethnea, and examined the
scientific writing styles in English from a two-fold perspective of linguistic
complexity: (1) syntactic complexity, including measurements of sentence length
and sentence complexity; and (2) lexical complexity, including measurements of
lexical diversity, lexical density, and lexical sophistication. The
observations suggest marginal differences between groups in syntactical and
lexical complexity.Comment: 6 figure
Natural language processing
Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems
MAG: A Multilingual, Knowledge-base Agnostic and Deterministic Entity Linking Approach
Entity linking has recently been the subject of a significant body of
research. Currently, the best performing approaches rely on trained
mono-lingual models. Porting these approaches to other languages is
consequently a difficult endeavor as it requires corresponding training data
and retraining of the models. We address this drawback by presenting a novel
multilingual, knowledge-based agnostic and deterministic approach to entity
linking, dubbed MAG. MAG is based on a combination of context-based retrieval
on structured knowledge bases and graph algorithms. We evaluate MAG on 23 data
sets and in 7 languages. Our results show that the best approach trained on
English datasets (PBOH) achieves a micro F-measure that is up to 4 times worse
on datasets in other languages. MAG, on the other hand, achieves
state-of-the-art performance on English datasets and reaches a micro F-measure
that is up to 0.6 higher than that of PBOH on non-English languages.Comment: Accepted in K-CAP 2017: Knowledge Capture Conferenc
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Reading Between the Lines: Using Citations to Understand Anthropologists’ Reading Patterns
Academic libraries want to collect the materials most useful to researchers, yet how can libraries know how successful they are? While Berkeley’s George and Mary Foster Anthropology Library collects data on which books circulate, it is difficult to evaluate how materials are actually being used to further the discipline of anthropology. In this article, we examine sources cited by our a) faculty members, b) dissertation writers, and c) honors thesis students to better understand how anthropologists read when conducting research. This paper compares materials used across subfields and research levels to highlight patterns in citations within this discipline, leading to new insights that will improve collection development among anthropology librarians
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