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Context-Aware Target Apps Selection and Recommendation for Enhancing Personal Mobile Assistants
Users install many apps on their smartphones, raising issues related to ...
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Guided Transformer: Leveraging Multiple External Sources for Representation Learning in Conversational Search
Asking clarifying questions in response to ambiguous or faceted queries ...
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Open-Retrieval Conversational Question Answering
Conversational search is one of the ultimate goals of information retrie...
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A Transformer-based Embedding Model for Personalized Product Search
Product search is an important way for people to browse and purchase ite...
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A Review-based Transformer Model for Personalized Product Search
In product search, customers make purchase decisions based on not only t...
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AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization
Redundancy-aware extractive summarization systems score the redundancy o...
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IART: Intent-aware Response Ranking with Transformers in Information-seeking Conversation Systems
Personal assistant systems, such as Apple Siri, Google Assistant, Amazon...
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Explainable Product Search with a Dynamic Relation Embedding Model
Product search is one of the most popular methods for customers to disco...
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A Study of Context Dependencies in Multi-page Product Search
In product search, users tend to browse results on multiple search resul...
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Conversational Product Search Based on Negative Feedback
Intelligent assistants change the way people interact with computers and...
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Leverage Implicit Feedback for Context-aware Product Search
Product search serves as an important entry point for online shopping. I...
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A Zero Attention Model for Personalized Product Search
Product search is one of the most popular methods for people to discover...
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Attentive History Selection for Conversational Question Answering
Conversational question answering (ConvQA) is a simplified but concrete ...
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Asking Clarifying Questions in Open-Domain Information-Seeking Conversations
Users often fail to formulate their complex information needs in a singl...
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ANTIQUE: A Non-Factoid Question Answering Benchmark
Considering the widespread use of mobile and voice search, answer passag...
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BERT with History Answer Embedding for Conversational Question Answering
Conversational search is an emerging topic in the information retrieval ...
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Investigating the Successes and Failures of BERT for Passage Re-Ranking
The bidirectional encoder representations from transformers (BERT) model...
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A Hybrid Retrieval-Generation Neural Conversation Model
Intelligent personal assistant systems, with either text-based or voice-...
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A Deep Look into Neural Ranking Models for Information Retrieval
Ranking models lie at the heart of research on information retrieval (IR...
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Learning to Selectively Transfer: Reinforced Transfer Learning for Deep Text Matching
Deep text matching approaches have been widely studied for many applicat...
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Iterative Relevance Feedback for Answer Passage Retrieval with Passage-level Semantic Match
Relevance feedback techniques assume that users provide relevance judgme...
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Revisiting Iterative Relevance Feedback for Document and Passage Retrieval
As more and more search traffic comes from mobile phones, intelligent as...
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Joint Modeling and Optimization of Search and Recommendation
Despite the somewhat different techniques used in developing search engi...
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Transfer Learning for Context-Aware Question Matching in Information-seeking Conversations in E-commerce
Building multi-turn information-seeking conversation systems is an impor...
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Towards Theoretical Understanding of Weak Supervision for Information Retrieval
Neural network approaches have recently shown to be effective in several...
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Distributed Evaluations: Ending Neural Point Metrics
With the rise of neural models across the field of information retrieval...
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WikiPassageQA: A Benchmark Collection for Research on Non-factoid Answer Passage Retrieval
With the rise in mobile and voice search, answer passage retrieval acts ...
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Cross Domain Regularization for Neural Ranking Models Using Adversarial Learning
Unlike traditional learning to rank models that depend on hand-crafted f...
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Target Apps Selection: Towards a Unified Search Framework for Mobile Devices
With the recent growth of conversational systems and intelligent assista...
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Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems
Intelligent personal assistant systems with either text-based or voice-b...
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Analyzing and Characterizing User Intent in Information-seeking Conversations
Understanding and characterizing how people interact in information-seek...
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Unbiased Learning to Rank with Unbiased Propensity Estimation
Learning to rank with biased click data is a well-known challenge. A var...
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Learning a Deep Listwise Context Model for Ranking Refinement
Learning to rank has been intensively studied and widely applied in info...
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aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model
As an alternative to question answering methods based on feature enginee...
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A Deep Relevance Matching Model for Ad-hoc Retrieval
In recent years, deep neural networks have led to exciting breakthroughs...
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Relevance-based Word Embedding
Learning a high-dimensional dense representation for vocabulary terms, a...
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Neural Ranking Models with Weak Supervision
Despite the impressive improvements achieved by unsupervised deep neural...
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Adaptability of Neural Networks on Varying Granularity IR Tasks
Recent work in Information Retrieval (IR) using Deep Learning models has...
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