Paper Group NANR 213
Selecting Domain-Specific Concepts for Question Generation With Lightly-Supervised Methods. Are Cohesive Features Relevant for Text Readability Evaluation?. Finding Recurrent Features of Image Schema Gestures: the FIGURE corpus. Measuring the Information Content of Financial News. Explicit Argument Identification for Discourse Parsing In Hindi: A H …
Selecting Domain-Specific Concepts for Question Generation With Lightly-Supervised Methods
| Title | Selecting Domain-Specific Concepts for Question Generation With Lightly-Supervised Methods |
| Authors | Yiping Jin, Phu Le |
| Abstract | |
| Tasks | Open Information Extraction, Question Generation, Reading Comprehension, Text Generation |
| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-6623/ |
| https://www.aclweb.org/anthology/W16-6623 | |
| PWC | https://paperswithcode.com/paper/selecting-domain-specific-concepts-for |
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Are Cohesive Features Relevant for Text Readability Evaluation?
| Title | Are Cohesive Features Relevant for Text Readability Evaluation? |
| Authors | Amalia Todirascu, Thomas Fran{\c{c}}ois, Delphine Bernhard, N{'u}ria Gala, Anne-Laure Ligozat |
| Abstract | This paper investigates the effectiveness of 65 cohesion-based variables that are commonly used in the literature as predictive features to assess text readability. We evaluate the efficiency of these variables across narrative and informative texts intended for an audience of L2 French learners. In our experiments, we use a French corpus that has been both manually and automatically annotated as regards to co-reference and anaphoric chains. The efficiency of the 65 variables for readability is analyzed through a correlational analysis and some modelling experiments. |
| Tasks | |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1094/ |
| https://www.aclweb.org/anthology/C16-1094 | |
| PWC | https://paperswithcode.com/paper/are-cohesive-features-relevant-for-text |
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Finding Recurrent Features of Image Schema Gestures: the FIGURE corpus
| Title | Finding Recurrent Features of Image Schema Gestures: the FIGURE corpus |
| Authors | Andy Luecking, Alex Mehler, er, D{'e}sir{'e}e Walther, Marcel Mauri, Dennis Kurf{"u}rst |
| Abstract | The Frankfurt Image GestURE corpus (FIGURE) is introduced. The corpus data is collected in an experimental setting where 50 naive participants spontaneously produced gestures in response to five to six terms from a total of 27 stimulus terms. The stimulus terms have been compiled mainly from image schemata from psycholinguistics, since such schemata provide a panoply of abstract contents derived from natural language use. The gestures have been annotated for kinetic features. FIGURE aims at finding (sets of) stable kinetic feature configurations associated with the stimulus terms. Given such configurations, they can be used for designing HCI gestures that go beyond pre-defined gesture vocabularies or touchpad gestures. It is found, for instance, that movement trajectories are far more informative than handshapes, speaking against purely handshape-based HCI vocabularies. Furthermore, the mean temporal duration of hand and arm movements associated vary with the stimulus terms, indicating a dynamic dimension not covered by vocabulary-based approaches. Descriptive results are presented and related to findings from gesture studies and natural language dialogue. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1227/ |
| https://www.aclweb.org/anthology/L16-1227 | |
| PWC | https://paperswithcode.com/paper/finding-recurrent-features-of-image-schema |
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Measuring the Information Content of Financial News
| Title | Measuring the Information Content of Financial News |
| Authors | Ching-Yun Chang, Yue Zhang, Zhiyang Teng, Zahn Bozanic, Bin Ke |
| Abstract | Measuring the information content of news text is useful for decision makers in their investments since news information can influence the intrinsic values of companies. We propose a model to automatically measure the information content given news text, trained using news and corresponding cumulative abnormal returns of listed companies. Existing methods in finance literature exploit sentiment signal features, which are limited by not considering factors such as events. We address this issue by leveraging deep neural models to extract rich semantic features from news text. In particular, a novel tree-structured LSTM is used to find target-specific representations of news text given syntax structures. Empirical results show that the neural models can outperform sentiment-based models, demonstrating the effectiveness of recent NLP technology advances for computational finance. |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1303/ |
| https://www.aclweb.org/anthology/C16-1303 | |
| PWC | https://paperswithcode.com/paper/measuring-the-information-content-of |
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Explicit Argument Identification for Discourse Parsing In Hindi: A Hybrid Pipeline
| Title | Explicit Argument Identification for Discourse Parsing In Hindi: A Hybrid Pipeline |
| Authors | Rohit Jain, Dipti Sharma |
| Abstract | |
| Tasks | Question Answering, Text Summarization |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-2010/ |
| https://www.aclweb.org/anthology/N16-2010 | |
| PWC | https://paperswithcode.com/paper/explicit-argument-identification-for |
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Kathaa : NLP Systems as Edge-Labeled Directed Acyclic MultiGraphs
| Title | Kathaa : NLP Systems as Edge-Labeled Directed Acyclic MultiGraphs |
| Authors | Sharada Mohanty, Nehal J Wani, Manish Srivastava, Dipti Sharma |
| Abstract | We present Kathaa, an Open Source web-based Visual Programming Framework for Natural Language Processing (NLP) Systems. Kathaa supports the design, execution and analysis of complex NLP systems by visually connecting NLP components from an easily extensible Module Library. It models NLP systems an edge-labeled Directed Acyclic MultiGraph, and lets the user use publicly co-created modules in their own NLP applications irrespective of their technical proficiency in Natural Language Processing. Kathaa exposes an intuitive web based Interface for the users to interact with and modify complex NLP Systems; and a precise Module definition API to allow easy integration of new state of the art NLP components. Kathaa enables researchers to publish their services in a standardized format to enable the masses to use their services out of the box. The vision of this work is to pave the way for a system like Kathaa, to be the Lego blocks of NLP Research and Applications. As a practical use case we use Kathaa to visually implement the Sampark Hindi-Panjabi Machine Translation Pipeline and the Sampark Hindi-Urdu Machine Translation Pipeline, to demonstrate the fact that Kathaa can handle really complex NLP systems while still being intuitive for the end user. |
| Tasks | Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-5201/ |
| https://www.aclweb.org/anthology/W16-5201 | |
| PWC | https://paperswithcode.com/paper/kathaa-nlp-systems-as-edge-labeled-directed |
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Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods
| Title | Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods |
| Authors | Lev Bogolubsky, Pavel Dvurechenskii, Alexander Gasnikov, Gleb Gusev, Yurii Nesterov, Andrei M. Raigorodskii, Aleksey Tikhonov, Maksim Zhukovskii |
| Abstract | In this paper, we consider a non-convex loss-minimization problem of learning Supervised PageRank models, which can account for features of nodes and edges. We propose gradient-based and random gradient-free methods to solve this problem. Our algorithms are based on the concept of an inexact oracle and unlike the state-of-the-art gradient-based method we manage to provide theoretically the convergence rate guarantees for both of them. Finally, we compare the performance of the proposed optimization methods with the state of the art applied to a ranking task. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6565-learning-supervised-pagerank-with-gradient-based-and-gradient-free-optimization-methods |
| http://papers.nips.cc/paper/6565-learning-supervised-pagerank-with-gradient-based-and-gradient-free-optimization-methods.pdf | |
| PWC | https://paperswithcode.com/paper/learning-supervised-pagerank-with-gradient |
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Automatic Construction of Large Readability Corpora
| Title | Automatic Construction of Large Readability Corpora |
| Authors | Jorge Alberto Wagner Filho, Rodrigo Wilkens, Aline Villavicencio |
| Abstract | This work presents a framework for the automatic construction of large Web corpora classified by readability level. We compare different Machine Learning classifiers for the task of readability assessment focusing on Portuguese and English texts, analysing the impact of variables like the feature inventory used in the resulting corpus. In a comparison between shallow and deeper features, the former already produce F-measures of over 0.75 for Portuguese texts, but the use of additional features results in even better results, in most cases. For English, shallow features also perform well as do classic readability formulas. Comparing different classifiers for the task, logistic regression obtained, in general, the best results, but with considerable differences between the results for two and those for three-classes, especially regarding the intermediary class. Given the large scale of the resulting corpus, for evaluation we adopt the agreement between different classifiers as an indication of readability assessment certainty. As a result of this work, a large corpus for Brazilian Portuguese was built, including 1.7 million documents and about 1.6 billion tokens, already parsed and annotated with 134 different textual attributes, along with the agreement among the various classifiers. |
| Tasks | Text Classification, Text Simplification |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4119/ |
| https://www.aclweb.org/anthology/W16-4119 | |
| PWC | https://paperswithcode.com/paper/automatic-construction-of-large-readability |
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Towards assessing depth of argumentation
| Title | Towards assessing depth of argumentation |
| Authors | Manfred Stede |
| Abstract | For analyzing argumentative text, we propose to study the {`}depth{'} of argumentation as one important component, which we distinguish from argument quality. In a pilot study with German newspaper commentary texts, we asked students to rate the degree of argumentativeness, and then looked for correlations with features of the annotated argumentation structure and the rhetorical structure (in terms of RST). The results indicate that the human judgements correlate with our operationalization of depth and with certain structural features of RST trees. | |
| Tasks | |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1312/ |
| https://www.aclweb.org/anthology/C16-1312 | |
| PWC | https://paperswithcode.com/paper/towards-assessing-depth-of-argumentation |
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| Framework | |
Machine Comprehension using Rich Semantic Representations
| Title | Machine Comprehension using Rich Semantic Representations |
| Authors | Mrinmaya Sachan, Eric Xing |
| Abstract | |
| Tasks | Natural Language Inference, Reading Comprehension |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-2079/ |
| https://www.aclweb.org/anthology/P16-2079 | |
| PWC | https://paperswithcode.com/paper/machine-comprehension-using-rich-semantic |
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Aligning Users Across Social Networks Using Network Embedding
| Title | Aligning Users Across Social Networks Using Network Embedding |
| Authors | Li Liu, William K. Cheung, Xin Li, Lejian Liao |
| Abstract | Li Liu,1 William K. Cheung,2 Xin Li,1⇤ and Lejian Liao1 |
| Tasks | Network Embedding |
| Published | 2016-06-09 |
| URL | https://dl.acm.org/citation.cfm?id=3060869 |
| https://www.ijcai.org/Proceedings/16/Papers/254.pdf | |
| PWC | https://paperswithcode.com/paper/aligning-users-across-social-networks-using |
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Corpus Fusion for Emotion Classification
| Title | Corpus Fusion for Emotion Classification |
| Authors | Suyang Zhu, Shoushan Li, Ying Chen, Guodong Zhou |
| Abstract | Machine learning-based methods have obtained great progress on emotion classification. However, in most previous studies, the models are learned based on a single corpus which often suffers from insufficient labeled data. In this paper, we propose a corpus fusion approach to address emotion classification across two corpora which use different emotion taxonomies. The objective of this approach is to utilize the annotated data from one corpus to help the emotion classification on another corpus. An Integer Linear Programming (ILP) optimization is proposed to refine the classification results. Empirical studies show the effectiveness of the proposed approach to corpus fusion for emotion classification. |
| Tasks | Emotion Classification |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1310/ |
| https://www.aclweb.org/anthology/C16-1310 | |
| PWC | https://paperswithcode.com/paper/corpus-fusion-for-emotion-classification |
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Results of the WNUT16 Named Entity Recognition Shared Task
| Title | Results of the WNUT16 Named Entity Recognition Shared Task |
| Authors | Benjamin Strauss, Bethany Toma, Alan Ritter, Marie-Catherine de Marneffe, Wei Xu |
| Abstract | This paper presents the results of the Twitter Named Entity Recognition shared task associated with W-NUT 2016: a named entity tagging task with 10 teams participating. We outline the shared task, annotation process and dataset statistics, and provide a high-level overview of the participating systems for each shared task. |
| Tasks | Named Entity Recognition |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-3919/ |
| https://www.aclweb.org/anthology/W16-3919 | |
| PWC | https://paperswithcode.com/paper/results-of-the-wnut16-named-entity |
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| Framework | |
Proceedings of the 5th Workshop on Vision and Language
| Title | Proceedings of the 5th Workshop on Vision and Language |
| Authors | |
| Abstract | |
| Tasks | |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-3200/ |
| https://www.aclweb.org/anthology/W16-3200 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-5th-workshop-on-vision-and |
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Proceedings of the 13th International Conference on Natural Language Processing
| Title | Proceedings of the 13th International Conference on Natural Language Processing |
| Authors | |
| Abstract | |
| Tasks | |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-6300/ |
| https://www.aclweb.org/anthology/W16-6300 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-13th-international-2 |
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