[PDF] Top 20 Modeling Topic Dependencies in Hierarchical Text Categorization
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Modeling Topic Dependencies in Hierarchical Text Categorization
... long-range dependencies lead to computational intractability or more in general to the problem of how to select an effective subset of ...the dependencies to be included in the model and (ii) their ... See full document
9
Large-scale Structural Reranking for Hierarchical Text Categorization
... Current hierarchical text categorization (HTC) methods mainly fall into three direc- tions: (1) Flat ...the hierarchical structure to decompose the entire problem into a set of smaller sub- ... See full document
146
Social Media Topic Categorization Using Hierarchical Clustering Approach
... Now in these days, the demand for internet based applications is growing continuously. A number of services and products are distributed using this medium i.e. e- commerce, internet banking, hotel reservation and others. ... See full document
8
Textual Relations and Topic Projection: Issues in Text Categorization
... the hierarchical orga- nization of the relations in a ...Functional dependencies existing between the statements, along with their respec- tive entailments, are represented with the aid of the ...as ... See full document
7
A Detailed Survey on Topic Modeling for Document and Short Text Data
... of text like web-pages, emails, study materials ...information. Topic modeling is a technique used to understand, summarize and organize the vast amount of textual ...data. Topic ... See full document
9
A Hierarchical Approach to Encoding Medical Concepts for Clinical Notes
... free text has attracted researchers in the Natural Lan- guage Processing (NLP) and Information Retrieval (IR) field for more than 10 ...hot topic in the clinical domain where categories to be assigned are ... See full document
6
Hierarchical vs. flat n-gram-based text categorization: can we do better?
... 21,578 text documents labelled by 135 categories which are not organized in hierarchical ...major topic and one (and only one) minor topic (or ...the topic of that document is set to ... See full document
20
Hiearchie: Visualization for Hierarchical Topic Models
... themselves. Topic modeling is a text understanding algorithm that discovers the “topics” or themes within a collection of ...on topic modeling become in- creasingly complex as the ... See full document
8
Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process
... pret text documents. Topic models consider doc- uments as a bag of ...formation, topic models formulate documents as mixtures of latent topics, where these topics are generated via the multinomial ... See full document
11
Modeling topic dependencies in semantically coherent text spans with copulas
... hand, text structure generally contains useful information that could be leveraged in inference ...definition text spans complete in themselves that convey a concise ...how text structure could help ... See full document
10
Topic Adaptation for Lecture Translation through Bilingual Latent Semantic Models
... that HM-BiTAM can generate unigram language models for both the source and target language and thus can be used for language model adaptation through MDI in a similar manner as outlined in Fed- erico (2002). Another ... See full document
9
Big Data Analytics Tools, Methods & Frameworks: A Comprehensive Review
... and topic modeling using Latent Dirichlet Allocation (LDA) for briefing the large text collection over MapReduce ...Different text summarization parameters like, compression ratio, retention ... See full document
6
Short Text Classification Based on Latent Topic Modeling and Word Embedding
... What is the reason for the unsatisfied performance? The secret lies on the feature selection of the short text and the lack of training corpus. For the intrinsic reason, the short texts have been transformed to ... See full document
7
Feature Space Restructuring for SVMs with Application to Text Categorization
... Using this method, we achieved high performance in text categorization both with small number and large numbers of labeled data... The task of text categorization has been exten- sively [r] ... See full document
7
Categorizing Research Papers By Topics Using Latent Dirichlet Allocation Model
... We use R Studio to generate a graph that depicts the distribution of topics over the documents. We are going to use add-on packages present in R such as ggplot2, reshape2, and lda. lda package implements latent Dirichlet ... See full document
5
Opinion Mining and Topic Categorization with Novel Term Weighting
... for text classifica- tion is vector space model. In this case text cat- egorization may be considered as a machine learning ...of text categori- zation with vector space model is compounded by the ... See full document
6
Social Media Text Data Visualization Modeling: A Timely Topic Score Technique
... refined topic (SMERT) for probabilistic clustering of texts to permit experts or users to edit the topics using knowledge about the system or their own needs [6, ... See full document
7
Generation of Hip Hop Lyrics with Hierarchical Modeling and Conditional Templates
... algorithmic modeling of the high- level creative process of song composition remains a challenge, we seek to improve the quality of the generated text by focusing on formal text proper- ...generating ... See full document
10
Topic Model Stability for Hierarchical Summarization
... Flat Topic Models Pairwise costs are assembled into a cost matrix indexed by (k, l) and the optimal cost assignment of the model pair is determined by the Hungarian assignment ...topics. Hierarchical ... See full document
10
An Entity Topic Model for Entity Linking
... shown in Figure 1, an EL system should identify the referent entities of the three mentions WWDC, Apple and Lion correspondingly are the entities Apple Worldwide Developers Conference, Apple Inc. and Mac OS X Lion in KB. ... See full document
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