Paper Group NANR 42
Understanding Medical free text: A Terminology driven approach. On the Recursive Teaching Dimension of VC Classes. The Storyline Annotation and Representation Scheme (StaR): A Proposal. Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats. Generating Coherent Summaries of Scientific Articles Using Coherence Patte …
Understanding Medical free text: A Terminology driven approach
| Title | Understanding Medical free text: A Terminology driven approach |
| Authors | Santosh Sai Krishna, Manoj Hans |
| Abstract | With many hospitals digitalizing clinical records it has opened opportunities for researchers in NLP, Machine Learning to apply techniques for extracting meaning and make actionable insights. There has been previous attempts in mapping free text to medical nomenclature like UMLS, SNOMED. However, in this paper, we had analyzed diagnosis in clinical reports using ICD10 to achieve a lightweight, real-time predictions by introducing concepts like WordInfo, root word identification. We were able to achieve 68.3{%} accuracy over clinical records collected from qualified clinicians. Our study would further help the healthcare institutes in organizing their clinical reports based on ICD10 mappings and derive numerous insights to achieve operational efficiency and better medical care. |
| Tasks | Boundary Detection |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4714/ |
| https://www.aclweb.org/anthology/W16-4714 | |
| PWC | https://paperswithcode.com/paper/understanding-medical-free-text-a-terminology |
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On the Recursive Teaching Dimension of VC Classes
| Title | On the Recursive Teaching Dimension of VC Classes |
| Authors | Xi Chen, Xi Chen, Yu Cheng, Bo Tang |
| Abstract | The recursive teaching dimension (RTD) of a concept class $C \subseteq {0, 1}^n$, introduced by Zilles et al. [ZLHZ11], is a complexity parameter measured by the worst-case number of labeled examples needed to learn any target concept of $C$ in the recursive teaching model. In this paper, we study the quantitative relation between RTD and the well-known learning complexity measure VC dimension (VCD), and improve the best known upper and (worst-case) lower bounds on the recursive teaching dimension with respect to the VC dimension. Given a concept class $C \subseteq {0, 1}^n$ with $VCD(C) = d$, we first show that $RTD(C)$ is at most $d 2^{d+1}$. This is the first upper bound for $RTD(C)$ that depends only on $VCD(C)$, independent of the size of the concept class $C$ and its~domain size $n$. Before our work, the best known upper bound for $RTD(C)$ is $O(d 2^d \log \log C)$, obtained by Moran et al. [MSWY15]. We remove the $\log \log C$ factor. We also improve the lower bound on the worst-case ratio of $RTD(C)$ to $VCD(C)$. We present a family of classes ${ C_k }_{k \ge 1}$ with $VCD(C_k) = 3k$ and $RTD(C_k)=5k$, which implies that the ratio of $RTD(C)$ to $VCD(C)$ in the worst case can be as large as $5/3$. Before our work, the largest ratio known was $3/2$ as obtained by Kuhlmann [Kuh99]. Since then, no finite concept class $C$ has been known to satisfy $RTD(C) > (3/2) VCD(C)$. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6412-on-the-recursive-teaching-dimension-of-vc-classes |
| http://papers.nips.cc/paper/6412-on-the-recursive-teaching-dimension-of-vc-classes.pdf | |
| PWC | https://paperswithcode.com/paper/on-the-recursive-teaching-dimension-of-vc |
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The Storyline Annotation and Representation Scheme (StaR): A Proposal
| Title | The Storyline Annotation and Representation Scheme (StaR): A Proposal |
| Authors | Tommaso Caselli, Piek Vossen |
| Abstract | |
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| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/W16-5708/ |
| https://www.aclweb.org/anthology/W16-5708 | |
| PWC | https://paperswithcode.com/paper/the-storyline-annotation-and-representation |
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Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats
| Title | Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats |
| Authors | Pulkit Tandon, Yash H. Malviya, Bipin Rajendran |
| Abstract | We demonstrate a spiking neural circuit for azimuth angle detection inspired by the echolocation circuits of the Horseshoe bat Rhinolophus ferrumequinum and utilize it to devise a model for navigation and target tracking, capturing several key aspects of information transmission in biology. Our network, using only a simple local-information based sensor implementing the cardioid angular gain function, operates at biological spike rate of 10 Hz. The network tracks large angular targets (60 degrees) within 1 sec with a 10% RMS error. We study the navigational ability of our model for foraging and target localization tasks in a forest of obstacles and show that our network requires less than 200X spike-triggered decisions, while suffering only a 1% loss in performance compared to a proportional-integral-derivative controller, in the presence of 50% additive noise. Superior performance can be obtained at a higher average spike rate of 100 Hz and 1000 Hz, but even the accelerated networks requires 20X and 10X lesser decisions respectively, demonstrating the superior computational efficiency of bio-inspired information processing systems. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6558-efficient-and-robust-spiking-neural-circuit-for-navigation-inspired-by-echolocating-bats |
| http://papers.nips.cc/paper/6558-efficient-and-robust-spiking-neural-circuit-for-navigation-inspired-by-echolocating-bats.pdf | |
| PWC | https://paperswithcode.com/paper/efficient-and-robust-spiking-neural-circuit |
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Generating Coherent Summaries of Scientific Articles Using Coherence Patterns
| Title | Generating Coherent Summaries of Scientific Articles Using Coherence Patterns |
| Authors | Daraksha Parveen, Mohsen Mesgar, Michael Strube |
| Abstract | |
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| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1074/ |
| https://www.aclweb.org/anthology/D16-1074 | |
| PWC | https://paperswithcode.com/paper/generating-coherent-summaries-of-scientific |
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Witness Identification in Twitter
| Title | Witness Identification in Twitter |
| Authors | Rui Fang, Armineh Nourbakhsh, Xiaomo Liu, Sameena Shah, Quanzhi Li |
| Abstract | |
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| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/W16-6210/ |
| https://www.aclweb.org/anthology/W16-6210 | |
| PWC | https://paperswithcode.com/paper/witness-identification-in-twitter |
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Dependency grammars as Haskell programs
| Title | Dependency grammars as Haskell programs |
| Authors | Tomasz Obr{\k{e}}bski |
| Abstract | |
| Tasks | Language Modelling |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-6310/ |
| https://www.aclweb.org/anthology/W16-6310 | |
| PWC | https://paperswithcode.com/paper/dependency-grammars-as-haskell-programs |
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Results of the 4th edition of BioASQ Challenge
| Title | Results of the 4th edition of BioASQ Challenge |
| Authors | Anastasia Krithara, Anastasios Nentidis, Georgios Paliouras, Ioannis Kakadiaris |
| Abstract | |
| Tasks | Information Retrieval, Question Answering |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-3101/ |
| https://www.aclweb.org/anthology/W16-3101 | |
| PWC | https://paperswithcode.com/paper/results-of-the-4th-edition-of-bioasq |
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SAWT: Sequence Annotation Web Tool
| Title | SAWT: Sequence Annotation Web Tool |
| Authors | Younes Samih, Wolfgang Maier, Laura Kallmeyer |
| Abstract | |
| Tasks | Tokenization |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/W16-5808/ |
| https://www.aclweb.org/anthology/W16-5808 | |
| PWC | https://paperswithcode.com/paper/sawt-sequence-annotation-web-tool |
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Bayesian Intermittent Demand Forecasting for Large Inventories
| Title | Bayesian Intermittent Demand Forecasting for Large Inventories |
| Authors | Matthias W. Seeger, David Salinas, Valentin Flunkert |
| Abstract | We present a scalable and robust Bayesian method for demand forecasting in the context of a large e-commerce platform, paying special attention to intermittent and bursty target statistics. Inference is approximated by the Newton-Raphson algorithm, reduced to linear-time Kalman smoothing, which allows us to operate on several orders of magnitude larger problems than previous related work. In a study on large real-world sales datasets, our method outperforms competing approaches on fast and medium moving items. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6313-bayesian-intermittent-demand-forecasting-for-large-inventories |
| http://papers.nips.cc/paper/6313-bayesian-intermittent-demand-forecasting-for-large-inventories.pdf | |
| PWC | https://paperswithcode.com/paper/bayesian-intermittent-demand-forecasting-for |
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E-TIPSY: Search Query Corpus Annotated with Entities, Term Importance, POS Tags, and Syntactic Parses
| Title | E-TIPSY: Search Query Corpus Annotated with Entities, Term Importance, POS Tags, and Syntactic Parses |
| Authors | Yuval Marton, Kristina Toutanova |
| Abstract | We present E-TIPSY, a search query corpus annotated with named Entities, Term Importance, POS tags, and SYntactic parses. This corpus contains crowdsourced (gold) annotations of the three most important terms in each query. In addition, it contains automatically produced annotations of named entities, part-of-speech tags, and syntactic parses for the same queries. This corpus comes in two formats: (1) Sober Subset: annotations that two or more crowd workers agreed upon, and (2) Full Glass: all annotations. We analyze the strikingly low correlation between term importance and syntactic headedness, which invites research into effective ways of combining these different signals. Our corpus can serve as a benchmark for term importance methods aimed at improving search engine quality and as an initial step toward developing a dataset of gold linguistic analysis of web search queries. In addition, it can be used as a basis for linguistic inquiries into the kind of expressions used in search. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1106/ |
| https://www.aclweb.org/anthology/L16-1106 | |
| PWC | https://paperswithcode.com/paper/e-tipsy-search-query-corpus-annotated-with |
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Analyzing the Effect of Entrainment on Dialogue Acts
| Title | Analyzing the Effect of Entrainment on Dialogue Acts |
| Authors | Masahiro Mizukami, Koichiro Yoshino, Graham Neubig, David Traum, Satoshi Nakamura |
| Abstract | |
| Tasks | |
| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-3640/ |
| https://www.aclweb.org/anthology/W16-3640 | |
| PWC | https://paperswithcode.com/paper/analyzing-the-effect-of-entrainment-on |
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TASTY: Interactive Entity Linking As-You-Type
| Title | TASTY: Interactive Entity Linking As-You-Type |
| Authors | Sebastian Arnold, Robert Dziuba, Alex L{"o}ser, er |
| Abstract | We introduce TASTY (Tag-as-you-type), a novel text editor for interactive entity linking as part of the writing process. Tasty supports the author of a text with complementary information about the mentioned entities shown in a {`}live{'} exploration view. The system is automatically triggered by keystrokes, recognizes mention boundaries and disambiguates the mentioned entities to Wikipedia articles. The author can use seven operators to interact with the editor and refine the results according to his specific intention while writing. Our implementation captures syntactic and semantic context using a robust end-to-end LSTM sequence learner and word embeddings. We demonstrate the applicability of our system in English and German language for encyclopedic or medical text. Tasty is currently being tested in interactive applications for text production, such as scientific research, news editorial, medical anamnesis, help desks and product reviews. | |
| Tasks | Entity Linking, Word Embeddings |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-2024/ |
| https://www.aclweb.org/anthology/C16-2024 | |
| PWC | https://paperswithcode.com/paper/tasty-interactive-entity-linking-as-you-type |
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Absolute and Relative Properties in Geographic Referring Expressions
| Title | Absolute and Relative Properties in Geographic Referring Expressions |
| Authors | Rodrigo de Oliveira, Somayajulu Sripada, Ehud Reiter |
| Abstract | |
| Tasks | Text Generation |
| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-6643/ |
| https://www.aclweb.org/anthology/W16-6643 | |
| PWC | https://paperswithcode.com/paper/absolute-and-relative-properties-in |
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SemEval-2016 Task 6: Detecting Stance in Tweets
| Title | SemEval-2016 Task 6: Detecting Stance in Tweets |
| Authors | Saif Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, Colin Cherry |
| Abstract | |
| Tasks | Information Retrieval, Natural Language Inference, Stance Detection, Text Summarization |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1003/ |
| https://www.aclweb.org/anthology/S16-1003 | |
| PWC | https://paperswithcode.com/paper/semeval-2016-task-6-detecting-stance-in |
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