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Document Ranking

10 papers with code ยท Natural Language Processing

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A Passage-Based Approach to Learning to Rank Documents

5 Jun 2019

Specifically, we devise a suite of learning-to-rank-based document retrieval methods that utilize an effective ranking of passages produced in response to the query; the passage ranking is also induced using a learning-to-rank approach.

DOCUMENT RANKING LEARNING-TO-RANK

Context Attentive Document Ranking and Query Suggestion

5 Jun 2019

We present a context-aware neural ranking model to exploit users' on-task search activities and enhance retrieval performance.

DOCUMENT RANKING

Unsupervised Neural Generative Semantic Hashing

3 Jun 2019

We present a novel unsupervised generative semantic hashing approach, \textit{Ranking based Semantic Hashing} (RBSH) that consists of both a variational and a ranking based component.

CODE GENERATION DOCUMENT RANKING INFORMATION RETRIEVAL

Understanding the Behaviors of BERT in Ranking

16 Apr 2019

This paper studies the performances and behaviors of BERT in ranking tasks.

DOCUMENT RANKING QUESTION ANSWERING

Learning Neural Representation for CLIR with Adversarial Framework

EMNLP 2018

In this paper, we follow the success of neural representation in natural language processing (NLP) and develop a novel text representation model based on adversarial learning, which seeks a task-specific embedding space for CLIR.

DOCUMENT RANKING INFORMATION RETRIEVAL MACHINE TRANSLATION REPRESENTATION LEARNING

Phrase2VecGLM: Neural generalized language model--based semantic tagging for complex query reformulation in medical IR

WS 2018

In this work, we develop a novel, completely unsupervised, neural language model-based document ranking approach to semantic tagging of documents, using the document to be tagged as a query into the GLM to retrieve candidate phrases from top-ranked related documents, thus associating every document with novel related concepts extracted from the text.

DOCUMENT RANKING INFORMATION RETRIEVAL KNOWLEDGE GRAPHS LANGUAGE MODELLING QUESTION ANSWERING

Jointly Embedding Entities and Text with Distant Supervision

WS 2018

Learning representations for knowledge base entities and concepts is becoming increasingly important for NLP applications.

DOCUMENT RANKING KNOWLEDGE BASE COMPLETION WORD EMBEDDINGS WORD SENSE DISAMBIGUATION

Learning to Rank from Samples of Variable Quality

21 Jun 2018

To this end, we introduce "fidelity-weighted learning" (FWL), a semi-supervised student-teacher approach for training deep neural networks using weakly-labeled data.

DOCUMENT RANKING LEARNING-TO-RANK