Construction of tagged corpus for Nanodevices development papers

Dieb, Thaer M.; Yoshioka, Masaharu; Hara, Shinjiro

doi:10.1109/grc.2011.6122587

Cited by 4 publications

(5 citation statements)

References 7 publications

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“…The extraction of experimental information is supposed to be applied as a preprocessing step for such shared data construction in nanoinformatics. Our preliminary work [36], [37], [38] is recognized as one of the main efforts in applying natural language processing to extract such information [39].…”

Section: Discussionmentioning

confidence: 99%

NaDev: An Annotated Corpus to Support Information Extraction from Research Papers on Nanocrystal Devices

Dieb¹,

Yoshioka²,

Hara

2016

Journal of Information Processing

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The process of nanocrystal device development is not well systematized. To support this process, analysis of the information produced by developmental experiments is required. In this study, we constructed an annotated corpus to support the extraction of experimental information from relevant publications. We designed the corpus-construction guidelines by cooperating with a domain expert. We evaluated these guidelines through corpusconstruction experiments with graduate students from this domain, and then evaluated the corpus with the domain expert. In the corpus construction experiments, we achieved a sufficient level of Inter-Annotator Agreement by using a loose agreement measure that ignored the term-boundary mismatch problem, and made an agreement corpus that excluded annotations based on misunderstanding the guidelines. The domain expert evaluated this agreement corpus and modified the guidelines based on real examples. Using these guidelines, we finalized the corpus called "NaDev" (Nanocrystal Device development corpus). The NaDev corpus and its construction guidelines will be released via our website, http://nanoinfo.ist.hokudai.ac.jp/. The NaDev corpus aims to support automatic information extraction from publications relevant to nanocrystal device development. This information can be used to solve problems in the nanotechnology domain using the massive availability of fresh information. To the best of our knowledge, this is the first corpus constructed for the development of nanocrystal devices.

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Section: Discussionmentioning

confidence: 99%

NaDev: An Annotated Corpus to Support Information Extraction from Research Papers on Nanocrystal Devices

Dieb¹,

Yoshioka²,

Hara

2016

Journal of Information Processing

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“…The NaDev corpus [ 27 – 28 ] was constructed to identify experimental information for extraction from nanocrystal device development papers. In order to extract wide varieties of experimental information, NaDev corpus uses full text of research papers instead of abstracts that are commonly used for constructing such corpora.…”

Section: Methodsmentioning

confidence: 99%

“…To support analysis of experimental results in this domain, extracting experimental information from related publications is desirable. We previously constructed an annotated corpus called “NaDev” ( Na nocrystal Dev ice Development corpus) [ 27 – 28 ] for research papers on nanocrystal device development. We also proposed a framework to extract information from research papers by using machine learning tools [ 29 – 30 ].…”

Section: Introductionmentioning

confidence: 99%

Framework for automatic information extraction from research papers on nanocrystal devices

Dieb¹,

Yoshioka²,

Hara³

et al. 2015

Beilstein J. Nanotechnol.

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SummaryTo support nanocrystal device development, we have been working on a computational framework to utilize information in research papers on nanocrystal devices. We developed an annotated corpus called “ NaDev” (Nanocrystal Device Development) for this purpose. We also proposed an automatic information extraction system called “NaDevEx” (Nanocrystal Device Automatic Information Extraction Framework). NaDevEx aims at extracting information from research papers on nanocrystal devices using the NaDev corpus and machine-learning techniques. However, the characteristics of NaDevEx were not examined in detail. In this paper, we conduct system evaluation experiments for NaDevEx using the NaDev corpus. We discuss three main issues: system performance, compared with human annotators; the effect of paper type (synthesis or characterization) on system performance; and the effects of domain knowledge features (e.g., a chemical named entity recognition system and list of names of physical quantities) on system performance. We found that overall system performance was 89% in precision and 69% in recall. If we consider identification of terms that intersect with correct terms for the same information category as the correct identification, i.e., loose agreement (in many cases, we can find that appropriate head nouns such as temperature or pressure loosely match between two terms), the overall performance is 95% in precision and 74% in recall. The system performance is almost comparable with results of human annotators for information categories with rich domain knowledge information (source material). However, for other information categories, given the relatively large number of terms that exist only in one paper, recall of individual information categories is not high (39–73%); however, precision is better (75–97%). The average performance for synthesis papers is better than that for characterization papers because of the lack of training examples for characterization papers. Based on these results, we discuss future research plans for improving the performance of the system.

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“…To support the nanodevice development process, we have proposed a framework [3] to add annotation information to research papers for extracting characteristic information about experiments in the nanodevice development process [4]. However, the quality of the annotated corpus was not good enough to construct an automatic information extraction system.…”

Section: Introductionmentioning

confidence: 99%

“…We previously proposed [3] an annotation framework to extract characteristic information related to nanodevice development experiments from research papers. Because information on source materials, experimental parameter settings, and evaluation criteria will help when analyzing the experimental results, and based on discussions with nanodevice development experts, we proposed using the following tag categories to annotate the corpus:…”

Section: A Introductionmentioning

confidence: 99%

Automatic Information Extraction of Experiments from Nanodevices Development Papers

Dieb

Yoshioka

Hara

2012

2012 IIAI International Conference on Advanced Applied Informatics

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To support development processes for nanodevices, we want to utilize the information related to experiments from nanodevice development research papers. In this paper, we propose a new guideline for constructing a tagged corpus of nanodevice development papers to achieve this goal. We also propose the use of a corpus construction support tool. To speed up the construction process, we propose an approach for automatic extraction of experiment-related information from the papers.

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Construction of tagged corpus for Nanodevices development papers

Cited by 4 publications

References 7 publications

NaDev: An Annotated Corpus to Support Information Extraction from Research Papers on Nanocrystal Devices

NaDev: An Annotated Corpus to Support Information Extraction from Research Papers on Nanocrystal Devices

Framework for automatic information extraction from research papers on nanocrystal devices

Automatic Information Extraction of Experiments from Nanodevices Development Papers

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