Matches in ScholarlyData for { ?s ?p ?o. }
- 299 sameAs 299.
- 299 abstract "Evaluation of Machine Translation (MT) technology is often tied to the requirement for tedious manual judgments of translation quality. While automated MT metrology continues to be an active area of research, a well known and often accepted standard metric is the manual human assessment of adequacy and fluency. There are several software packages that have been used to facilitate these judgments, but for the 2008 NIST Open MT Evaluation, NIST s Speech Group created an online software tool to accommodate the requirement for centralized data and distributed judges. This paper introduces the NIST TAP-ET application and reviews the reasoning underlying its design. Where available, analysis of data sets judged for Adequacy and Preference using the TAP-ET application will be presented. TAP-ET is freely available and ready to download, and contains a variety of customizable features.".
- 299 hasAuthorList authorList.
- 299 hasTopic Linguistics.
- 299 isPartOf proceedings.
- 299 keyword "Evaluation methodologies".
- 299 keyword "Machine Translation, SpeechToSpeech Translation".
- 299 keyword "Tools, systems, applications".
- 299 title "Translation Adequacy and Preference Evaluation Tool (TAP-ET)".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
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- item-1 type ListItem.
- item-1 hasContent mark-przybocki.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent kay-peterson.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent sebastien-bronsart.
- item-3 previous item-2.
- 30 creator mikko-lounela.
- 30 type InProceedings.
- 30 label "Process Model for Composing High-quality Text Corpora".
- 30 sameAs 30.
- 30 abstract "The Teko corpus composing model offers a decentralized, dynamic way of collecting high-quality text corpora for linguistic research. The resulting corpus consists of independent text sets. The sets are composed in cooperation with linguistic research projects, so each of them responds to a specific research need. The corpora are morphologically annotated and XML-based, with in-built compatibilty with the Kaino user interface used in the corpus server of the Research Institute for the Languages of Finland. Furthermore, software for extracting standard quantitative reports from the text sets has been created during the project. The paper describes the project, and estimates its benefits and problems. It also gives an overview of the technical qualities of the corpora and corpus interface connected to the Teko project.".
- 30 hasAuthorList authorList.
- 30 hasTopic Linguistics.
- 30 isPartOf proceedings.
- 30 keyword "Corpus (creation, annotation, etc.)".
- 30 keyword "LR Infrastructures and Architectures".
- 30 keyword "LR web services".
- 30 title "Process Model for Composing High-quality Text Corpora".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasLastItem item-1.
- item-1 type ListItem.
- item-1 hasContent mikko-lounela.
- 300 creator dominic-widdows.
- 300 creator kathleen-ferraro.
- 300 type InProceedings.
- 300 label "Semantic Vectors: a Scalable Open Source Package and Online Technology Management Application".
- 300 sameAs 300.
- 300 abstract "This paper describes the open source SemanticVectors package that efficiently creates semantic vectors for words and documents from a corpus of free text articles. We believe that this package can play an important role in furthering research in distributional semantics, and (perhaps more importantly) can help to significantly reduce the current gap that exists between good research results and valuable applications in production software. Two clear principles that have guided the creation of the package so far include ease-of-use and scalability. The basic package installs and runs easily on any Java-enabled platform, and depends only on Apache Lucene. Dimension reduction is performed using Random Projection, which enables the system to scale much more effectively than other algorithms used for the same purpose. This paper also describes a trial application in the Technology Management domain, which highlights some user-centred design challenges which we believe are also key to successful deployment of this technology.".
- 300 hasAuthorList authorList.
- 300 hasTopic Linguistics.
- 300 isPartOf proceedings.
- 300 keyword "Acquisition, Machine Learning".
- 300 keyword "Document Classification, Text categorisation".
- 300 keyword "Tools, systems, applications".
- 300 title "Semantic Vectors: a Scalable Open Source Package and Online Technology Management Application".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
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- item-1 type ListItem.
- item-1 hasContent dominic-widdows.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent kathleen-ferraro.
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- 301 creator hiroyuki-shinnou.
- 301 creator minoru-sasaki.
- 301 type InProceedings.
- 301 label "Division of Example Sentences Based on the Meaning of a Target Word Using Semi-Supervised Clustering".
- 301 sameAs 301.
- 301 abstract "In this paper, we describe a system that divides example sentences (data set) into clusters, based on the meaning of the target word, using a semi-supervised clustering technique. In this task, the estimation of the cluster number (the number of the meaning) is critical. Our system primarily concentrates on this aspect. First, a user assigns the system an initial cluster number for the target word. The system then performs general clustering on the data set to obtain small clusters. Next, using constraints given by the user, the system integrates these clusters to obtain the final clustering result. Our system performs this entire procedure with high precision and requiring only a few constraints. In the experiment, we tested the system for 12 Japanese nouns used in the SENSEVAL2 Japanese dictionary task. The experiment proved the effectiveness of our system. In the future, we will improve sentence similarity measurements.".
- 301 hasAuthorList authorList.
- 301 hasTopic Linguistics.
- 301 isPartOf proceedings.
- 301 keyword "Corpus (creation, annotation, etc.)".
- 301 keyword "Tools, systems, applications".
- 301 keyword "Word Sense Disambiguation".
- 301 title "Division of Example Sentences Based on the Meaning of a Target Word Using Semi-Supervised Clustering".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasLastItem item-2.
- item-1 type ListItem.
- item-1 hasContent hiroyuki-shinnou.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent minoru-sasaki.
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- 303 creator cristina-mota.
- 303 creator ralph-grishman.
- 303 type InProceedings.
- 303 label "Is this NE tagger getting old?".
- 303 sameAs 303.
- 303 abstract "This paper focuses on the influence of changing the text time frame on the performance of a named entity tagger. We followed a twofold approach to investigate this subject: on the one hand, we analyzed a corpus that spans 8 years, and, on the other hand, we assessed the performance of a name tagger trained and tested on that corpus. We created 8 samples from the corpus, each drawn from the articles for a particular year. In terms of corpus analysis, we calculated the corpus similarity and names shared between samples. To see the effect on tagger performance, we implemented a semi-supervised name tagger based on co-training; then, we trained and tested our tagger on those samples. We observed that corpus similarity, names shared between samples, and tagger performance all decay as the time gap between the samples increases. Furthermore, we observed that the corpus similarity and names shared correlate with the tagger F-measure. These results show that named entity recognition systems may become obsolete in a short period of time.".
- 303 hasAuthorList authorList.
- 303 hasTopic Linguistics.
- 303 isPartOf proceedings.