[PDF] Top 20 Learning to Rank Semantic Coherence for Topic Segmentation
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Learning to Rank Semantic Coherence for Topic Segmentation
... develops topic modeling tech- niques to explore topic representation of text and topic change between textual segments (Yam- ron et ...algorithm, topic models are able to model ... See full document
5
Topic Segmentation with a Structured Topic Model
... or topic distributions instead of word frequency can significantly improve segmen- tation ...vanced topic models that model dependencies be- tween (sub-)sections in a document, such as struc- tured ... See full document
11
Contextually Mediated Semantic Similarity Graphs for Topic Segmentation
... topical coherence using long-range influence of terms and a contextually determined measure of semantic ...of semantic relatedness reinforces global co- occurrence statistics with local contextual ... See full document
9
Gestural Cohesion for Topic Segmentation
... The motivation for this approach comes from a series of psycholinguistic studies suggesting that gesture supplements speech with meaningful and unique semantic content (McNeill, 1992; Kendon, 2004). We assume that ... See full document
9
Automatic Evaluation of Topic Coherence
... for learning sets of words (aka topics) which capture the latent semantics of a document or document collection, in the form of methods such as latent semantic analysis (Deerwester et ...text ... See full document
9
Learning to Rank Question Answer Pairs Using Hierarchical Recurrent Encoder with Latent Topic Clustering
... latent topic clustering mod- ...latent topic clustering mod- ule extracts semantic information from tar- get ...nearest topic cluster, thus helping the neural network model ana- lyze the ... See full document
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Are Semantically Coherent Topic Models Useful for Ad Hoc Information Retrieval?
... perspective, topic models seem attractive in the sense that they can provide a descriptive and intu- itive representation of ...the semantic coherence of topic models (Newman et ...of ... See full document
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Automatic quantification of superficial foveal avascular zone in optical coherence tomography angiography implemented with deep learning
... Conv-BN-ReLu block comprised two convolutional layers (Conv), two BN layers, and two ReLu layers (ReLu). The SE block included one pooling layer, one re- shape layer (Reshape), two dense layers (Dense), one ReLu layer, ... See full document
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Distributional Lexical Entailment by Topic Coherence
... to rank hypernyms above other re- lation ...of Topic Coherence measures. Recent Semantic Relation Classification shared tasks (SemEval-2010 Task 8, SemEval-2012 Task 2) are also relevant, ... See full document
9
Evaluating Topic Coherence Using Distributional Semantics
... the topic word space is used there is a consistent improvement in performance compared to the average PMI (Newman et ...the topic words is ...reduced semantic space are higher than average PMI and ... See full document
9
Broadcast News Story Segmentation Using Manifold Learning on Latent Topic Distributions
... some topic model techniques which provide conceptu- al level matching have been introduced to text and story segmentation task (Hearst, ...latent semantic analysis (PLSA) (Hofman- n, 1999) is a ... See full document
6
Optimizing Semantic Coherence in Topic Models
... both topic size (top) and our coher- ence metric ...for topic size vs. 0.94 for coherence and AUC 0.79 for topic size ...this topic bad”. Using topic size alone as a predic- tor ... See full document
11
Bayesian Unsupervised Topic Segmentation
... This paper presents a novel Bayesian approach to unsupervised topic segmentation. Our algorithm is capable of incorporating both lexical cohesion and cue phrase features in a principled manner, and out- ... See full document
10
Statistical Models for Topic Segmentation
... To reiterate, we used our word frequency model with a total of 3 parameters trained from English newswire text to segment Spanish broadcast news data.. regions of a document unless those[r] ... See full document
8
Exploiting Social Information in Grounded Language Learning via Grammatical Reduction
... Why would the child’s own gaze be more impor- tant than the caregiver’s? Perhaps caregivers are fol- lowing in, i.e., talking about objects that their chil- dren are interested in (Baldwin, 1991). However, an- other ... See full document
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Modeling Topic Coherence for Speech Recognition
... Modeling Topic Coherence for Speech Recognition Modeling Topic Coherence for Speech Recognition S a t o s h i S e k i n e C o m p u t e r Scion( (; ] ) e I ) a i ' t m c n t N e w Y o r k U n i v e r[.] ... See full document
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Learning Fully Dense Neural Networks for Image Semantic Segmentation
... Another way to deal with this problem is to reuse the feature maps with rich spatial information of earlier layers. U-Net (Ronneberger, Fischer, and Brox 2015) exploits previous feature maps in the decoder module by a ... See full document
8
A Novel Measure for Coherence in Statistical Topic Models
... corpora. Topic mod- eling algorithms help understand the un- derlying patterns, or “topics”, in ...concept, coherence, when assessing the topics and propose an effective method for its ...of ... See full document
6
Automatic Evaluation of Local Topic Quality
... global topic-word distribu- tions that typically make sense to users and serve to give a good high-level overview of the general themes and trends in the ...cal topic assignments can be ...typical ... See full document
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