ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1903.10675
  4. Cited By
Document Similarity for Texts of Varying Lengths via Hidden Topics

Document Similarity for Texts of Varying Lengths via Hidden Topics

26 March 2019
Hongyu Gong
Tarek Sakakini
S. Bhat
Jinjun Xiong
ArXivPDFHTML

Papers citing "Document Similarity for Texts of Varying Lengths via Hidden Topics"

7 / 7 papers shown
Title
A prototype-based model for set classification
A prototype-based model for set classification
Mohammad Mohammadi
Sreejita Ghosh
VLM
112
1
0
25 Aug 2024
Semantic Similarity Measure of Natural Language Text through Machine
  Learning and a Keyword-Aware Cross-Encoder-Ranking Summarizer -- A Case Study
  Using UCGIS GIS&T Body of Knowledge
Semantic Similarity Measure of Natural Language Text through Machine Learning and a Keyword-Aware Cross-Encoder-Ranking Summarizer -- A Case Study Using UCGIS GIS&T Body of Knowledge
Yuanyuan Tian
Wenwen Li
Sizhe Wang
Zhining Gu
24
3
0
17 May 2023
Multi-Vector Models with Textual Guidance for Fine-Grained Scientific
  Document Similarity
Multi-Vector Models with Textual Guidance for Fine-Grained Scientific Document Similarity
Sheshera Mysore
Arman Cohan
Tom Hope
11
39
0
16 Nov 2021
The Devil is in the Details: Evaluating Limitations of Transformer-based
  Methods for Granular Tasks
The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks
Brihi Joshi
Neil Shah
Francesco Barbieri
Leonardo Neves
39
5
0
02 Nov 2020
PaRe: A Paper-Reviewer Matching Approach Using a Common Topic Space
PaRe: A Paper-Reviewer Matching Approach Using a Common Topic Space
Omer Anjum
Hongyu Gong
S. Bhat
Wen-mei W. Hwu
Jinjun Xiong
15
31
0
25 Sep 2019
Assessing the Difficulty of Classifying ConceptNet Relations in a
  Multi-Label Classification Setting
Assessing the Difficulty of Classifying ConceptNet Relations in a Multi-Label Classification Setting
Maria Becker
Michael Staniek
Vivi Nastase
Anette Frank
18
10
0
14 May 2019
Word Mover's Embedding: From Word2Vec to Document Embedding
Word Mover's Embedding: From Word2Vec to Document Embedding
Lingfei Wu
Ian En-Hsu Yen
Kun Xu
Fangli Xu
Avinash Balakrishnan
Pin-Yu Chen
Pradeep Ravikumar
Michael Witbrock
15
106
0
30 Oct 2018
1