[PDF] Top 20 Computational Models for Event Type Classification in Context
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Computational Models for Event Type Classification in Context
... A sample of 40 Italian verbs have been selected for their high degree of prototipicality with respect to the four event types in table 1 (10 verbs for each category). Following the approach in Lagus and Airola ... See full document
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Computational models of trust
... The Histos model [74] is an enhancement to Sporas that takes into account the group dynamics as in Regret [63]. In particular, Histos looks at the links between users (in a social network) to deduce personalised ... See full document
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A Proposal for a Coherence Corpus in Machine Translation
... Previous computational models for assessing coherence in a monolingual context have covered entity transitions (Barzilay and Lapata, 2008; El- sner and Charniak, 2011; Burstein et ... See full document
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An Integrated Approach for Image Inpainting Based On Saliency Detection
... scene classification, image registration and so ...existing computational models are designed based on computer vision techniques by using lots of image cues and ...global context, spatially ... See full document
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Building Context aware Clause Representations for Situation Entity Type Classification
... network models, including Convolution Neural Network (CNN) (Wang and Lu, 2017), Recurrent Neural Network (RNN) based models (Wang et ...Sequence models (Vaswani et ... See full document
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Some issues in marginal recurrent event Cox type models
... Metcalfe and Thompson (2007) raise the question of whether the WLW model should be applied. They look at the differences of the WLW and PWP models in simulation studies and with real data. Their view point is that ... See full document
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Using Context Events in Neural Network Models for Event Temporal Status Identification
... CNN models using dependency chains as input consistently outperform the corresponding mod- els using local ...cal context based CNN model (Huang et ...status classification F-scores by 4 and 10 ... See full document
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Feature Selection Using a Semantic Hierarchy for Event Recognition and Type Classification
... the context defined by a five- word window [-2, +2] around a target ...the context is defined by syntactic dependencies. This feature type differs from WF because the context may go beyond the ... See full document
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TimeML Events Recognition and Classification: Learning CRF Models with Semantic Roles
... and classification has been pointed out to be very important to improve com- plex natural language processing (NLP) applica- tions such as automatic summarization (Daniel et ...the context of summarization, ... See full document
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Structure of pauses in speech in the context of speaker verification and classification of speech type
... situational context and cognitive task and therefore it could find appli- cation for automatic discourse analysis and conversation modeling ...statistical models of pauses will be a fundament for studying ... See full document
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Comparison of risks of cardiovascular events in the elderly using standard survival analysis and multiple-events and recurrent-events methods
... time-to-first- event model with approaches that take into account multiple cardiovascular burden and/or recurrency in the context of a prospective cohort study- the Cardio- vascular Health Study ...survival ... See full document
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Fuel Type Classification in the Mediterranean Basin Context: State of the Art and Future Research
... Mediterranean type-ecosystem 3 ...historic event linked to the importance of understanding the patterns of diversity in Mediterranean Basin is associated to the climatic oscillations that occurred since the ... See full document
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Simple computational methods for the analysis of (s, s) type inventory models
... inventory models, wherein the number of units demanded at successive demand epochs are Markov dependent as introduced by Krishnamoothy and Lakshmi (1991), is ... See full document
8
User Type Classification of Tweets with Implications for Event Recognition
... that type. Using five-fold cross- validation, we train separate models for person- and ...During event recogni- tion, we first apply our user type classifier to a tweet and then apply the ... See full document
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Topic Models for Meaning Similarity in Context
... a context as we extract only patterns containing tar- get words together with their X and Y ...The models assign similarity scores to each candidate by comparing them to the pattern occurring in the ... See full document
9
Context-dependent sound event detection
... acoustic models are trained using audio signals where the start and end times of events as well as their classes have manually been ...each event instance annotated represents one training sample for the ... See full document
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Automatic Linguistic Classification
... 1965 International Conference on Computational Linguistics AUTOMATIC LINGUISTIC CLASSIFICATION 6 1965 International Conference on Computational Linguistics AUTOmaTIC LINGUISTIC CLASSIFICATION E D Pend[.] ... See full document
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Article Title & Authors
... regression models, based on a large number of predictors, to indicate that these models cannot outperform the (benchmark) autoregressive model in forecasting the Dow Jones Islamic Market Index (DJIM) ... See full document
15
Vector space semantics with frequency driven motifs
... tion strengths (through counts and PMI scores) of word neighbourhoods, they disregard much of the regularity in human language. Most significantly, word tokens that act as latent dimensions are of- ten derived from ... See full document
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Exploiting Sentence and Context Representations in Deep Neural Models for Spoken Language Understanding
... We propose in this paper a semantic decoder that learns from unaligned data (Figure 1) and that exploits rich semantic distributed word representations instead of delexicalisation. The semantic decoder predicts the ... See full document
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