📰 Joint Conference on Lexical and Computational Semantics (*SEM), Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity 2013: all accepted papers

45 papers · the most cited first · ← Joint Conference on Lexical and Computational Semantics (*SEM), Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity 2013

1. *SEM 2013 shared task: Semantic Textual SimilarityEneko Agirre, Daniel Cer, Mona Diab et al.our summary
2. A Dataset of Syntactic-Ngrams over Time from a Very Large Corpus of English BooksYoav Goldberg, Jon Orwantour summary
3. Automatically Identifying Implicit Arguments to Improve Argument Linking and Coherence ModelingMichael Roth, Anette Frank
4. BUT-TYPED: Using domain knowledge for computing typed similarityLubomir Otrusina, Pavel Smrz
5. Bootstrapping Semantic Role Labelers from Parallel DataMikhail Kozhevnikov, Ivan Titov
6. CFILT-CORE: Semantic Textual Similarity using Universal Networking LanguageAvishek Dan, Pushpak Bhattacharyya
7. CLaC-CORE: Exhaustive Feature Combination for Measuring Textual SimilarityEhsan Shareghi, Sabine Bergler
8. CNGL-CORE: Referential Translation Machines for Measuring Semantic SimilarityErgun Biçici, Josef van Genabith
9. CPN-CORE: A Text Semantic Similarity System Infused with Opinion KnowledgeCarmen Banea, Yoonjung Choi, Lingjia Deng et al.
10. Choosing the Right Words: Characterizing and Reducing Error of the Word Count ApproachHansen Andrew Schwartz, Johannes Eichstaedt, Eduardo Blanco et al.
11. Coarse to Fine Grained Sense Disambiguation in WikipediaHui Shen, Razvan Bunescu, Rada Mihalcea
12. DLS@CU-CORE: A Simple Machine Learning Model of Semantic Textual SimilarityMd. Sultan, Steven Bethard, Tamara Sumner
13. DeepPurple: Lexical, String and Affective Feature Fusion for Sentence-Level Semantic Similarity EstimationNikolaos Malandrakis, Elias Iosif, Vassiliki Prokopi et al.
14. Distinguishing Common and Proper NounsJudita Preiss, Mark Stevenson
15. ECNUCS: Measuring Short Text Semantic Equivalence Using Multiple Similarity MeasurementsTiantian Zhu, Lan Man
16. Exploring Vector Space Models to Predict the Compositionality of German Noun-Noun CompoundsSabine Schulte im Walde, Stefan Müller, Stefan Roller
17. HENRY-CORE: Domain Adaptation and Stacking for Text SimilarityMichael Heilman, Nitin Madnani
18. IBM_EG-CORE: Comparing multiple Lexical and NE matching features in measuring Semantic Textual similaritySara Noeman
19. INAOE_UPV-CORE: Extracting Word Associations from Document Corpora to estimate Semantic Textual SimilarityFernando Sánchez-Vega, Manuel Montes-y-Gómez, Paolo Rosso et al.
20. KLUE-CORE: A regression model of semantic textual similarityPaul Greiner, Thomas Proisl, Stefan Evert et al.
21. KnCe2013-CORE:Semantic Text Similarity by use of Knowledge BasesHermann Ziak, Roman Kern
22. LIPN-CORE: Semantic Text Similarity using n-grams, WordNet, Syntactic Analysis, ESA and Information Retrieval based FeaturesDavide Buscaldi, Joseph Le Roux, Jorge J. García Flores et al.
23. MayoClinicNLP–CORE: Semantic representations for textual similarityStephen Wu, Dongqing Zhu, Ben Carterette et al.
24. Metaphor Identification as InterpretationEkaterina Shutova
25. Montague Meets Markov: Deep Semantics with Probabilistic Logical FormIslam Beltagy, Cuong Chau, Gemma Boleda et al.
26. More Words and Bigger PicturesDavid Forsyth
27. NTNU-CORE: Combining strong features for semantic similarityErwin Marsi, Hans Moen, Lars Bungum et al.
28. PolyUCOMP-CORE_TYPED: Computing Semantic Textual Similarity using Overlapped SensesJian Xu, Qin Lu
29. Predicting the Compositionality of Multiword Expressions Using Translations in Multiple LanguagesBahar Salehi, Paul Cook
30. SOFTCARDINALITY-CORE: Improving Text Overlap with Distributional Measures for Semantic Textual SimilaritySergio Jimenez, Claudia Becerra, Alexander Gelbukh
31. SRIUBC-Core: Multiword Soft Similarity Models for Textual SimilarityEric Yeh
32. SXUCFN-Core: STS Models Integrating FrameNet Parsing InformationSai Wang, Ru Li, Ruibo Wang et al.
33. Semantic Parsing Freebase: Towards Open-domain Semantic ParsingQingqing Cai, Alexander Yates
34. Towards a Formal Distributional Semantics: Simulating Logical Calculi with TensorsEdward Grefenstette
35. UBC_UOS-TYPED: Regression for typed-similarityEneko Agirre, Nikolaos Aletras, Aitor Gonzalez-Agirre et al.
36. UCAM-CORE: Incorporating structured distributional similarity into STSTamara Polajnar, Laura Rimell, Douwe Kiela
37. UMBC_EBIQUITY-CORE: Semantic Textual Similarity SystemsLushan Han, Abhay L. Kashyap, Tim Finin et al.our summary
38. UMCC_DLSI: Textual Similarity based on Lexical-Semantic featuresAlexander Chávez, Héctor Dávila, Yoan Gutiérrez et al.
39. UNIBA-CORE: Combining Strategies for Semantic Textual SimilarityAnnalina Caputo, Pierpaolo Basile, Giovanni Semeraro
40. UNITOR-CORE_TYPED: Combining Text Similarity and Semantic Filters through SV RegressionDanilo Croce, Valerio Storch, Roberto Basili
41. UPC-CORE: What Can Machine Translation Evaluation Metrics and Wikipedia Do for Estimating Semantic Textual Similarity?Alberto Barrón-Cedeño, Lluís Màrquez, Maria Fuentes et al.
42. UniMelb_NLP-CORE: Integrating predictions from multiple domains and feature sets for estimating semantic textual similaritySpandana Gella, Bahar Salehi, Marco Lui et al.
43. Unsupervised Word Usage Similarity in Social Media TextsSpandana Gella, Paul Cook, Bo Han
44. Using the text to evaluate short answers for reading comprehension exercisesAndrea Horbach, Alexis Palmer, Manfred Pinkal
45. iKernels-Core: Tree Kernel Learning for Textual SimilarityAliaksei Severyn, Massimo Nicosia, Alessandro Moschitti

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