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Ad-Hoc Information Retrieval

18 papers with code · Natural Language Processing

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MatchZoo: A Toolkit for Deep Text Matching

23 Jul 2017faneshion/MatchZoo

In recent years, deep neural models have been widely adopted for text matching tasks, such as question answering and information retrieval, showing improved performance as compared with previous methods.

AD-HOC INFORMATION RETRIEVAL INFORMATION RETRIEVAL QUESTION ANSWERING TEXT MATCHING

Text Matching as Image Recognition

20 Feb 2016NTMC-Community/MatchZoo

An effective way is to extract meaningful matching patterns from words, phrases, and sentences to produce the matching score.

AD-HOC INFORMATION RETRIEVAL TEXT MATCHING

IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models

30 May 2017geek-ai/irgan

This paper provides a unified account of two schools of thinking in information retrieval modelling: the generative retrieval focusing on predicting relevant documents given a query, and the discriminative retrieval focusing on predicting relevancy given a query-document pair.

AD-HOC INFORMATION RETRIEVAL DOCUMENT RANKING INFORMATION RETRIEVAL QUESTION ANSWERING

End-to-End Neural Ad-hoc Ranking with Kernel Pooling

20 Jun 2017AdeDZY/K-NRM

Given a query and a set of documents, K-NRM uses a translation matrix that models word-level similarities via word embeddings, a new kernel-pooling technique that uses kernels to extract multi-level soft match features, and a learning-to-rank layer that combines those features into the final ranking score.

AD-HOC INFORMATION RETRIEVAL DOCUMENT RANKING LEARNING-TO-RANK WORD EMBEDDINGS

Deep Relevance Ranking Using Enhanced Document-Query Interactions

EMNLP 2018 nlpaueb/deep-relevance-ranking

We explore several new models for document relevance ranking, building upon the Deep Relevance Matching Model (DRMM) of Guo et al. (2016).

AD-HOC INFORMATION RETRIEVAL QUESTION ANSWERING

Learning to Match Using Local and Distributed Representations of Text for Web Search

Proceedings of the 26th International Conference on World Wide Web, WWW '17 2017 bmitra-msft/NDRM

Models such as latent semantic analysis and those based on neural embeddings learn distributed representations of text, and match the query against the document in the latent semantic space.

AD-HOC INFORMATION RETRIEVAL DOCUMENT RANKING INFORMATION RETRIEVAL

Co-PACRR: A Context-Aware Neural IR Model for Ad-hoc Retrieval

30 Jun 2017khui/copacrr

Neural IR models, such as DRMM and PACRR, have achieved strong results by successfully capturing relevance matching signals.

AD-HOC INFORMATION RETRIEVAL