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Adapting ranking SVM to document retrieval
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Searching the web: The public and their queries
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The Elements of Statistical Learning
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
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From e-sex to e-commerce: Web search changes
inferredcites →https://doi.org/10.1145/1008992.1009006openalex-snapshot
Discriminative models for information retrieval
inferredcites →https://doi.org/10.1145/1076034.1076085openalex-snapshot
Linear discriminant model for information retrieval
inferredcites →https://doi.org/10.1145/1102351.1102363openalex-snapshot
Learning to rank using gradient descent
inferredcites →https://doi.org/10.1145/1102351.1102370openalex-snapshot
New approaches to support vector ordinal regression
inferredcites →https://doi.org/10.1145/1143844.1143981openalex-snapshot
Collaborative ordinal regression
inferredcites →https://doi.org/10.1145/1273496openalex-snapshot
Proceedings of the 24th international conference on Machine learning
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A language modeling approach to information retrieval
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A Language Modeling Approach to Information Retrieval
inferredcites →https://doi.org/10.1145/3130348.3130374openalex-snapshot
IR evaluation methods for retrieving highly relevant documents
inferredcites →https://doi.org/10.1145/3130348.3130375openalex-snapshot
Document Language Models, Query Models, and Risk Minimization for Information Retrieval
inferredcites →https://doi.org/10.1145/345508.345545openalex-snapshot
IR evaluation methods for retrieving highly relevant documents
inferredcites →https://doi.org/10.1145/383952.383970openalex-snapshot
Document language models, query models, and risk minimization for information retrieval
inferredcites →https://doi.org/10.1145/775047.775067openalex-snapshot
Optimizing search engines using clickthrough data
inferredcites →https://doi.org/10.7551/mitpress/1113.003.0010openalex-snapshot
Large Margin Rank Boundaries for Ordinal Regression
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Learning SVM Ranking Functions from User Feedback Using Document Metadata and Active Learning in the Biomedical Domain
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Generalization Analysis for Ranking
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Information Retrieval and Web Search
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Ontology Similarity Measure by Optimizing NDCG Measure and Application in Physics Education
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Image Search Reranking with Transductive Learning to Rank Framework
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Bibliometric study of the scientific research on “Learning to Rank” between 2000 and 2013
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A survey on literature based discovery approaches in biomedical domain
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Enumerative feature subset based ranking system for learning to rank in presence of implicit user feedback
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Learning semantic representation with neural networks for community question answering retrieval
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Non-parallel hyperplanes ordinal regression machine
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Expert list-wise ranking method based on sparse learning
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HyperSSR: A hypergraph based semi-supervised ranking method for visual search reranking
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Multi-task ranking SVM for image cosegmentation
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Deep top similarity hashing with class-wise loss for multi-label image retrieval
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Top-rank convolutional neural network and its application to medical image-based diagnosis
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Evolution of ICTs-empowered-identification: A general re-ranking method for person re-identification
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Chemical-induced gene expression ranking and its application to pancreatic cancer drug repurposing
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SemRank: ranking refinement strategy by using the semantic intensity
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Query-Level Stability of IRSVM for Replacement Case
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An Approach to Incremental Deep Web Crawling Based on Incremental Harvest Model
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Prescriptive analytics of electric bus battery allocation optimization based on the Plackett-Luce model
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The Problem of Sentiment Analysis
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Document Sentiment Classification
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Sentence Subjectivity and Sentiment Classification
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Aspect Sentiment Classification
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Aspect and Entity Extraction
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Sentiment Lexicon Generation
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Analysis of Comparative Opinions
inferred← citeshttps://doi.org/10.1017/9781108639286.010openalex-snapshot
Opinion Summarization and Search
inferred← citeshttps://doi.org/10.1017/9781108639286.011openalex-snapshot
Analysis of Debates and Comments
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Detecting Fake or Deceptive Opinions
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The Problem of Sentiment Analysis
inferred← citeshttps://doi.org/10.1017/cbo9781139084789.004openalex-snapshot
Document Sentiment Classification
inferred← citeshttps://doi.org/10.1017/cbo9781139084789.005openalex-snapshot
Sentence Subjectivity and Sentiment Classification
inferred← citeshttps://doi.org/10.1017/cbo9781139084789.006openalex-snapshot
Aspect Sentiment Classification
inferred← citeshttps://doi.org/10.1017/cbo9781139084789.007openalex-snapshot
Aspect and Entity Extraction
inferred← citeshttps://doi.org/10.1017/cbo9781139084789.008openalex-snapshot
Sentiment Lexicon Generation
inferred← citeshttps://doi.org/10.1017/cbo9781139084789.009openalex-snapshot
Analysis of Comparative Opinions
inferred← citeshttps://doi.org/10.1017/cbo9781139084789.010openalex-snapshot
Opinion Summarization and Search
inferred← citeshttps://doi.org/10.1017/cbo9781139084789.011openalex-snapshot
Analysis of Debates and Comments
inferred← citeshttps://doi.org/10.1017/cbo9781139084789.013openalex-snapshot
Detecting Fake or Deceptive Opinions
inferred← citeshttps://doi.org/10.1017/s1351324919000032openalex-snapshot
A learning to rank approach for cross-language information retrieval exploiting multiple translation resources
inferred← citeshttps://doi.org/10.1038/s41598-022-10383-wopenalex-snapshot
Learning to rank Higgs boson candidates
inferred← citeshttps://doi.org/10.1080/01621459.2016.1215988openalex-snapshot
On Theoretically Optimal Ranking Functions in Bipartite Ranking
inferred← citeshttps://doi.org/10.1080/03610926.2026.2666192openalex-snapshot
Support vector regression with imprecise observations based on ε -Huber loss function
inferred← citeshttps://doi.org/10.1080/08839514.2015.983014openalex-snapshot
A Novel Crossing Minimization Ranking Method
inferred← citeshttps://doi.org/10.1088/1742-6596/1913/1/012150openalex-snapshot
Information Retrieval using Machine learning for Ranking: A Review
inferred← citeshttps://doi.org/10.1093/comjnl/bxw034openalex-snapshot
Logics, Lattices and Probability: The Missing Links to Information Retrieval
inferred← citeshttps://doi.org/10.1109/access.2019.2894701openalex-snapshot
Extracting Emotion Causes Using Learning to Rank Methods From an Information Retrieval Perspective
inferred← citeshttps://doi.org/10.1109/access.2023.3296850openalex-snapshot
HSM-QA: Question Answering System Based on Hierarchical Semantic Matching
inferred← citeshttps://doi.org/10.1109/aicai.2019.8701391openalex-snapshot
Information Retrieval Ranking Using Machine Learning Techniques
inferred← citeshttps://doi.org/10.1109/apsipa.2014.7041591openalex-snapshot
A margin-based discriminative modeling approach for extractive speech summarization
inferred← citeshttps://doi.org/10.1109/besc.2015.7365953openalex-snapshot
Learning to rank domain experts in microblogging by combining text and non-text features
inferred← citeshttps://doi.org/10.1109/bibm.2015.7359729openalex-snapshot
Learning to rank for biomedical information retrieval
inferred← citeshttps://doi.org/10.1109/bibm.2018.8621577openalex-snapshot
Improve Diversity-oriented Biomedical Information Retrieval using Supervised Query Expansion
inferred← citeshttps://doi.org/10.1109/bigdata.2017.8258078openalex-snapshot
What is skipped: Finding desirable items in e-commerce search by discovering the worst title tokens
inferred← citeshttps://doi.org/10.1109/bigdata.2017.8258135openalex-snapshot
A comparative study on learning to rank with computational methods
inferred← citeshttps://doi.org/10.1109/bigdia51454.2020.00022openalex-snapshot
Data-driven approach with artificial neural network for Global Innovation Index re-evaluation
inferred← citeshttps://doi.org/10.1109/cibcb.2007.4221239openalex-snapshot
Super Granular SVM Feature Elimination (Super GSVM-FE) Model for Protein Sequence Motif Informnation Extraction
inferred← citeshttps://doi.org/10.1109/crv.2016.39openalex-snapshot
Learning Neural Networks with Ranking-Based Losses for Action Retrieval
inferred← citeshttps://doi.org/10.1109/csse.2008.720openalex-snapshot
Learning to Rank with Bayesian Evidence Framework
inferred← citeshttps://doi.org/10.1109/cvpr.2008.4587352openalex-snapshot
Multiple-instance ranking: Learning to rank images for image retrieval
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