Paper Group NANR 221
Syntactic analyses and named entity recognition for PubMed and PubMed Central — up-to-the-minute. PARSEME Survey on MWE Resources. Reconstructing Parameters of Spreading Models from Partial Observations. Optimizing an Approximation of ROUGE - a Problem-Reduction Approach to Extractive Multi-Document Summarization. Physical Causality of Action Ver …
Syntactic analyses and named entity recognition for PubMed and PubMed Central — up-to-the-minute
| Title | Syntactic analyses and named entity recognition for PubMed and PubMed Central — up-to-the-minute |
| Authors | Kai Hakala, Suwisa Kaewphan, Tapio Salakoski, Filip Ginter |
| Abstract | |
| Tasks | Named Entity Recognition, Part-Of-Speech Tagging, Tokenization |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2913/ |
| https://www.aclweb.org/anthology/W16-2913 | |
| PWC | https://paperswithcode.com/paper/syntactic-analyses-and-named-entity |
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PARSEME Survey on MWE Resources
| Title | PARSEME Survey on MWE Resources |
| Authors | Gyri Sm{\o}rdal Losnegaard, Federico Sangati, Carla Parra Escart{'\i}n, Agata Savary, Sascha Bargmann, Johanna Monti |
| Abstract | This paper summarizes the preliminary results of an ongoing survey on multiword resources carried out within the IC1207 Cost Action PARSEME (PARSing and Multi-word Expressions). Despite the availability of language resource catalogs and the inventory of multiword datasets on the SIGLEX-MWE website, multiword resources are scattered and difficult to find. In many cases, language resources such as corpora, treebanks, or lexical databases include multiwords as part of their data or take them into account in their annotations. However, these resources need to be centralized to make them accessible. The aim of this survey is to create a portal where researchers can easily find multiword(-aware) language resources for their research. We report on the design of the survey and analyze the data gathered so far. We also discuss the problems we have detected upon examination of the data as well as possible ways of enhancing the survey. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1364/ |
| https://www.aclweb.org/anthology/L16-1364 | |
| PWC | https://paperswithcode.com/paper/parseme-survey-on-mwe-resources |
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Reconstructing Parameters of Spreading Models from Partial Observations
| Title | Reconstructing Parameters of Spreading Models from Partial Observations |
| Authors | Andrey Lokhov |
| Abstract | Spreading processes are often modelled as a stochastic dynamics occurring on top of a given network with edge weights corresponding to the transmission probabilities. Knowledge of veracious transmission probabilities is essential for prediction, optimization, and control of diffusion dynamics. Unfortunately, in most cases the transmission rates are unknown and need to be reconstructed from the spreading data. Moreover, in realistic settings it is impossible to monitor the state of each node at every time, and thus the data is highly incomplete. We introduce an efficient dynamic message-passing algorithm, which is able to reconstruct parameters of the spreading model given only partial information on the activation times of nodes in the network. The method is generalizable to a large class of dynamic models, as well to the case of temporal graphs. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6129-reconstructing-parameters-of-spreading-models-from-partial-observations |
| http://papers.nips.cc/paper/6129-reconstructing-parameters-of-spreading-models-from-partial-observations.pdf | |
| PWC | https://paperswithcode.com/paper/reconstructing-parameters-of-spreading-models-1 |
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Optimizing an Approximation of ROUGE - a Problem-Reduction Approach to Extractive Multi-Document Summarization
| Title | Optimizing an Approximation of ROUGE - a Problem-Reduction Approach to Extractive Multi-Document Summarization |
| Authors | Maxime Peyrard, Judith Eckle-Kohler |
| Abstract | |
| Tasks | Document Summarization, Multi-Document Summarization |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1172/ |
| https://www.aclweb.org/anthology/P16-1172 | |
| PWC | https://paperswithcode.com/paper/optimizing-an-approximation-of-rouge-a |
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Physical Causality of Action Verbs in Grounded Language Understanding
| Title | Physical Causality of Action Verbs in Grounded Language Understanding |
| Authors | Qiaozi Gao, Malcolm Doering, Shaohua Yang, Joyce Chai |
| Abstract | |
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| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1171/ |
| https://www.aclweb.org/anthology/P16-1171 | |
| PWC | https://paperswithcode.com/paper/physical-causality-of-action-verbs-in |
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Learning Text Pair Similarity with Context-sensitive Autoencoders
| Title | Learning Text Pair Similarity with Context-sensitive Autoencoders |
| Authors | Hadi Amiri, Philip Resnik, Jordan Boyd-Graber, Hal Daum{'e} III |
| Abstract | |
| Tasks | Representation Learning, Semantic Textual Similarity |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1177/ |
| https://www.aclweb.org/anthology/P16-1177 | |
| PWC | https://paperswithcode.com/paper/learning-text-pair-similarity-with-context |
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GWU NLP at SemEval-2016 Shared Task 1: Matrix Factorization for Crosslingual STS
| Title | GWU NLP at SemEval-2016 Shared Task 1: Matrix Factorization for Crosslingual STS |
| Authors | Hanan Aldarmaki, Mona Diab |
| Abstract | |
| Tasks | Semantic Textual Similarity, Word Embeddings |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1101/ |
| https://www.aclweb.org/anthology/S16-1101 | |
| PWC | https://paperswithcode.com/paper/gwu-nlp-at-semeval-2016-shared-task-1-matrix |
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Yandex School of Data Analysis approach to English-Turkish translation at WMT16 News Translation Task
| Title | Yandex School of Data Analysis approach to English-Turkish translation at WMT16 News Translation Task |
| Authors | Anton Dvorkovich, Sergey Gubanov, Irina Galinskaya |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2311/ |
| https://www.aclweb.org/anthology/W16-2311 | |
| PWC | https://paperswithcode.com/paper/yandex-school-of-data-analysis-approach-to |
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A Scalable Approach for Outlier Detection in Edge Streams Using Sketch-based Approximations
| Title | A Scalable Approach for Outlier Detection in Edge Streams Using Sketch-based Approximations |
| Authors | Stephen Ranshous, Steve Harenberg, Kshitij Sharma, Nagiza F. Samatova |
| Abstract | Dynamic graphs are a powerful way to model an evolving set of objects and their ongoing interactions. A broad spectrum of systems, such as information, communication, and social, are naturally represented by dynamic graphs. Outlier (or anomaly) detection in dynamic graphs can provide unique insights into the relationships of objects and identify novel or emerging relationships. To date, outlier detection in dynamic graphs has been studied in the context of graph streams, focusing on the analysis and comparison of entire graph objects. However, the volume and velocity of data are necessitating a transition from outlier detection in the context of graph streams to outlier detection in the context of edge streams–where the stream consists of individual graph edges instead of entire graph objects. In this paper, we propose the first approach for outlier detection in edge streams. We first describe a high-level model for outlier detection based on global and local structural properties of a stream. We then propose a novel application of the Count-Min sketch for approximating these properties, and prove probabilistic error bounds on our edge outlier scoring functions. Our sketch-based implementation provides a scalable solution, having constant time updates and constant space requirements. Experiments on synthetic and real-world datasets demonstrate our method’s scalability, effectiveness for discovering outliers, and the effects of approximation. |
| Tasks | Anomaly Detection, Anomaly Detection in Edge Streams, Outlier Detection |
| Published | 2016-05-07 |
| URL | https://epubs.siam.org/doi/pdf/10.1137/1.9781611974348.22 |
| https://epubs.siam.org/doi/pdf/10.1137/1.9781611974348.22 | |
| PWC | https://paperswithcode.com/paper/a-scalable-approach-for-outlier-detection-in |
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English Resource Semantics
| Title | English Resource Semantics |
| Authors | Dan Flickinger, Emily M. Bender, Woodley Packard |
| Abstract | |
| Tasks | Machine Translation, Natural Language Inference, Question Generation, Sentiment Analysis, Word Embeddings |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-4001/ |
| https://www.aclweb.org/anthology/N16-4001 | |
| PWC | https://paperswithcode.com/paper/english-resource-semantics |
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Post Retraction Citations in Context
| Title | Post Retraction Citations in Context |
| Authors | Gali Halevi, Judit Bar-Ilan |
| Abstract | |
| Tasks | Information Retrieval |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-1503/ |
| https://www.aclweb.org/anthology/W16-1503 | |
| PWC | https://paperswithcode.com/paper/post-retraction-citations-in-context |
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The More Antecedents, the Merrier: Resolving Multi-Antecedent Anaphors
| Title | The More Antecedents, the Merrier: Resolving Multi-Antecedent Anaphors |
| Authors | Hardik Vala, Andrew Piper, Derek Ruths |
| Abstract | |
| Tasks | Coreference Resolution |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1216/ |
| https://www.aclweb.org/anthology/P16-1216 | |
| PWC | https://paperswithcode.com/paper/the-more-antecedents-the-merrier-resolving |
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Topic Extraction from Microblog Posts Using Conversation Structures
| Title | Topic Extraction from Microblog Posts Using Conversation Structures |
| Authors | Jing Li, Ming Liao, Wei Gao, Yulan He, Kam-Fai Wong |
| Abstract | |
| Tasks | Topic Models |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1199/ |
| https://www.aclweb.org/anthology/P16-1199 | |
| PWC | https://paperswithcode.com/paper/topic-extraction-from-microblog-posts-using |
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A Fast Approach for Semantic Similar Short Texts Retrieval
| Title | A Fast Approach for Semantic Similar Short Texts Retrieval |
| Authors | Yanhui Gu, Zhenglu Yang, Junsheng Zhou, Weiguang Qu, Jinmao Wei, Xingtian Shi |
| Abstract | |
| Tasks | |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-2015/ |
| https://www.aclweb.org/anthology/P16-2015 | |
| PWC | https://paperswithcode.com/paper/a-fast-approach-for-semantic-similar-short |
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Use of Domain-Specific Language Resources in Machine Translation
| Title | Use of Domain-Specific Language Resources in Machine Translation |
| Authors | Sanja {\v{S}}tajner, Andreia Querido, Nuno Rendeiro, Jo{~a}o Ant{'o}nio Rodrigues, Ant{'o}nio Branco |
| Abstract | In this paper, we address the problem of Machine Translation (MT) for a specialised domain in a language pair for which only a very small domain-specific parallel corpus is available. We conduct a series of experiments using a purely phrase-based SMT (PBSMT) system and a hybrid MT system (TectoMT), testing three different strategies to overcome the problem of the small amount of in-domain training data. Our results show that adding a small size in-domain bilingual terminology to the small in-domain training corpus leads to the best improvements of a hybrid MT system, while the PBSMT system achieves the best results by adding a combination of in-domain bilingual terminology and a larger out-of-domain corpus. We focus on qualitative human evaluation of the output of two best systems (one for each approach) and perform a systematic in-depth error analysis which revealed advantages of the hybrid MT system over the pure PBSMT system for this specific task. |
| Tasks | Machine Translation |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1094/ |
| https://www.aclweb.org/anthology/L16-1094 | |
| PWC | https://paperswithcode.com/paper/use-of-domain-specific-language-resources-in |
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