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Vector space model
Document and Topic Models: Plsa
Redalyc.Latent Dirichlet Allocation Complement in the Vector Space Model for Multi-Label Text Classification
Evaluating Vector-Space Models of Word Representation, Or, the Unreasonable Effectiveness of Counting Words Near Other Words
Gensim Is Robust in Nature and Has Been in Use in Various Systems by Various People As Well As Organisations for Over 4 Years
Deconstructing Word Embedding Models
Vector Space Models for Words and Documents Statistical Natural Language Processing ELEC-E5550 Jan 30, 2019 Tiina Lindh-Knuutila D.Sc
Word Embeddings: History & Behind the Scene
UNIVERSITY of CALIFORNIA, SAN DIEGO Bag-Of-Concepts As a Movie
Analysis of a Vector Space Model, Latent Semantic Indexing and Formal Concept Analysis for Information Retrieval
Ontology Alignment Based on Word Embedding and Random Forest Classification
A Structured Vector Space Model for Word Meaning in Context
Graph-Based Word Embedding Learning and Cross-Lingual Contextual Word Embedding Learning Zheng Zhang
Feature Extraction Using Latent Dirichlet Allocation and Neural Networks: a Case Study on Movie Synopses
Vector Space Model
Vector Space Representations in Information Retrieval
A Review on Wordnet and Vector Space Analysis for Short-Text Semantic Similarity
Gensim Documentation Release 0.6.0
Software Framework for Topic Modelling with Large Corpora
Top View
A Systematic Study of Semantic Vector Space Model Parameters
An Effective Information Retrieval for Ambiguous Query
Mathematical Foundations Behind Latent Semantic Analysis
Evaluating Vector-Space Models of Analogy Dawn Chen (
[email protected]
) Joshua C
Vector Space Model
Comparing Latent Dirichlet Allocation and Latent Semantic Analysis As Classifiers
Evaluation of the Shapd2 Algorithm Efficiency in Plagiarism Detection Task Using Pan Plagiarism Corpus
ES-ESA: an Information Retrieval Prototype Using Explicit Semantic Analysis and Elasticsearch
A Dual Embedding Space Model for Document Ranking
Distinguishing Antonyms from Synonyms in Vector Space Models of Semantics
Modeling Musical Context Using Word2vec
Latent Semantic Indexing: an Overview
A Generalized Vector Space Model for Text Retrieval Based on Semantic Relatedness
Evaluating Vector Space Models Using Human Semantic Priming Results
Learning Latent Vector Spaces for Product Search
Latent Dirichlet Allocation: Extracting Topics from Software Engineering Data
Comparison of Vector Space Representations of Documents for the Task of Matching Contents of Educational Course Programmes
Evaluating Word Embedding Models: Methods and Experimental Results
Concept-Based Information Retrieval Using Explicit Semantic Analysis
CONSTRUCTION of COMPACT RETRIEVAL MODELS Unifying Framework and Analysis
VECTOR SPACE MODELS: • Relies on NLP Methods Already Seen INFORMATION RETRIEVAL and LEXICAL • Big field: Small Taster Here SEMANTICS • Link to Today’S General Topic: •
Ranking Streaming Data with Continuous Queries
Semantic Representations in Text Data 1
Plagiarism Detection on Electronic Text Based Assignments Using Vector Space Model
Word Embedding Models As Graphs
Latent Semantic Analysis (LSA)
Semantic Representation Using Explicit Concept Space Models
Augmenting Word Embeddings with Unsupervised Relation Vectors
A Structured Vector Space Model for Word Meaning in Context
A Survey of Word Embedding Literature: Context Representations and the Challenge of Ambiguity
INSTITUT F¨UR INFORMATIK a Semantic Search Engine for Tagged
Vector Semantics and Embeddings
Latent Dirichlet Allocation Complement in the Vector Space Model for Multi-Label Text Classification
Learning Bag-Of-Embedded-Words Representations for Textual Information Retrieval
Latent Semantic Analysis
Easyesa: a Low-Effort Infrastructure for Explicit Semantic Analysis
COMP90042 Lecture 10