Filters








3,893 Hits in 9.1 sec

Conversational AI over Military Scenarios Using Intent Detection and Response Generation

Hsiu-Min Chuang, Ding-Wei Cheng
2022 Applied Sciences  
This work focused on developing conversational systems based on the Chinese corpus over military scenarios.  ...  The goal of the NLG phase, in contrast, is to provide answers or ask questions to clarify the user's needs.  ...  This model performed question-answer and semantics-named entity matching within its knowledge base and then selected the optimal strategy for response generation.  ... 
doi:10.3390/app12052494 fatcat:cndhbcko5vehfb44y2eiqyrbe4

Statistical Machine Translation for Query Expansion in Answer Retrieval

Stefan Riezler, Alexander Vasserman, Ioannis Tsochantaridis, Vibhu O. Mittal, Yi Liu
2007 Annual Meeting of the Association for Computational Linguistics  
SMT model trained on question-answer pairs.  ...  SMT-based query expansion is done by i) using a full-sentence paraphraser to introduce synonyms in context of the entire query, and ii) by translating query terms into answer terms using a full-sentence  ...  In contrast, the mean reciprocal rank (MRR) measure standardly used in QA can have the effect of preferring systems that find answers only for a small set of queries, but rank them higher than systems  ... 
dblp:conf/acl/RiezlerVTML07 fatcat:ixaktrrskfcqraia3fxl55aghi

Adaptable Closed-Domain Question Answering Using Contextualized CNN-Attention Models and Question Expansion

Mahsa Abazari Kia, Aygul Garifullina, Mathias Kern, Jon Chamberlain, Shoaib Jameel
2022 IEEE Access  
In closed-domain Question Answering (QA), the goal is to retrieve answers to questions within a specific domain.  ...  Moreover, we include candidate answer identification and question expansion techniques for context reduction and rewriting ambiguous questions.  ...  [20] proposed an integrated framework for answering Chinese questions in restricted domains by modeling the question pair, comparing the input question to the existing question, and then identifying  ... 
doi:10.1109/access.2022.3170466 fatcat:64rbm4tiqfb3hi4law253ioina

Report on the SIGIR 2008 workshop on focused retrieval

Jaap Kamps, Shlomo Geva, Andrew Trotman
2008 SIGIR Forum  
Nine paper were presented in three sessions and in a fourth session-joint with the SIGIR 2008 Workshop on Aggregate Search-there was a panel discussion.  ...  On July 24, 2008 the SIGIR Workshop on Focused Retrieval was held as part of SIGIR in Singapore.  ...  Final thanks are due to the paper authors, the panelists, and the participants for a great and lively workshop. Some of the authors contributed to this report prior to submission.  ... 
doi:10.1145/1480506.1480517 fatcat:6jestvkydrg4ff6lbqebfc4yoa

PerCQA: Persian Community Question Answering Dataset [article]

Naghme Jamali, Yadollah Yaghoobzadeh, Hesham Faili
2021 arXiv   pre-print
We also build strong benchmarks for the task of answer selection in PerCQA by using mono- and multi-lingual pre-trained language models  ...  Automatic answer selection, answer ranking, question retrieval, expert finding, and fact-checking are example learning tasks performed using CQA data.  ...  Novelty based ranking of human answers for coder for sentence similarity modeling in answer se- community questions. In Proceedings of the 39th In- lection task.  ... 
arXiv:2112.13238v1 fatcat:bdonom4a3fdqpengmncnxgxmfi

Multi-CPR

Dingkun Long, Qiong Gao, Kuan Zou, Guangwei Xu, Pengjun Xie, Ruijie Guo, Jian Xu, Guanjun Jiang, Luxi Xing, Ping Yang
2022 Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval  
Therefore, in this paper, we present a novel multi-domain Chinese dataset for passage retrieval (Multi-CPR).  ...  However, in the Chinese field, especially for specific domains, passage retrieval systems are still immature due to quality-annotated dataset being limited by scale.  ...  Special thanks to Shuyi Li and Qiankun Sun for their efforts as expert examiners in the annotation process.  ... 
doi:10.1145/3477495.3531736 fatcat:dhnei3zrpfas3doimagef6vzfm

Multi-CPR: A Multi Domain Chinese Dataset for Passage Retrieval [article]

Dingkun Long, Qiong Gao, Kuan Zou, Guangwei Xu, Pengjun Xie, Ruijie Guo, Jian Xu, Guanjun Jiang, Luxi Xing, Ping Yang
2022 arXiv   pre-print
Therefore, in this paper, we present a novel multi-domain Chinese dataset for passage retrieval (Multi-CPR).  ...  However, in the Chinese field, especially for specific domains, passage retrieval systems are still immature due to quality-annotated dataset being limited by scale.  ...  Special thanks to Shuyi Li and Qiankun Sun for their efforts as expert examiners in the annotation process.  ... 
arXiv:2203.03367v2 fatcat:wjvdvmxmvrcuzfwuzh4agrh37u

Statistical source expansion for question answering

Nico Schlaefer, Jennifer Chu-Carroll, Eric Nyberg, James Fan, Wlodek Zadrozny, David Ferrucci
2011 Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11  
The statistical models use a comprehensive set of features to predict the topicality and quality of text nuggets based on topic models built from seed content, search engine rankings and surface characteristics  ...  While the expanded corpus is not intended for human consumption, it can be leveraged in question answering (QA) and other information retrieval or extraction tasks to find more relevant knowledge and to  ...  For each question q i in a test set (i = 1, ..., n) let r i be the rank of the first correct answer in the list of candidates generated by a QA system for that question, if one has been found.  ... 
doi:10.1145/2063576.2063632 dblp:conf/cikm/SchlaeferCNFZF11 fatcat:whoy62klazctbdo4p57wbevkdu

A survey on semantic question answering systems

Christina Antoniou, Nick Bassiliades
2022 Knowledge engineering review (Print)  
The purpose of this survey is to identify the common features and approaches of the semantic question answering (SQA) systems, although many different and prototype systems have been designed.  ...  Recently, many question answering systems that derive answers from linked data repositories have been developed.  ...  All SQA system use semantic graph-based models. Our values for this criterion are algebraic models, probability models, semantic graph-based models, and theoretic models.  ... 
doi:10.1017/s0269888921000138 fatcat:3aml27j2ezcppgq3dq3qhe5dqe

Triple-to-Text Generation with an Anchor-to-Prototype Framework

Ziran Li, Zibo Lin, Ning Ding, Hai-Tao Zheng, Ying Shen
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
Generating a textual description from a set of RDF triplets is a challenging task in natural language generation.  ...  The model retrieves a set of prototype descriptions from the training data and extracts writing patterns from them to guide the generation process.  ...  For example, Figure 1 shows one question that was answered incorrectly by the states-of-thearts ranking-based approach 2 .  ... 
doi:10.24963/ijcai.2020/519 dblp:conf/ijcai/ChenLHQ20 fatcat:jomkkkx42bdwtallumrfgvthwm

TCAR at TAC-KBP 2009

Patrick Schone, Alan Goldschen, C. Langley, S. Lewis, Boyan A. Onyshkevych, R. Cutts, B. Dawson, Craig Pfeifer, M. Ursiak, J. MacBride, G. Matrangola, C. McDonough
2009 Text Analysis Conference  
The TCAR team developed multiple systems in just a matter of weeks for both participating in the TAC-KBP evaluation under the entity linking and the slot filling paradigms.  ...  made use of our question answering system and the latter exploited relation-finding from a number of our content extraction systems.  ...  The system next re-ranks the initial set of Wikipedia nodes provided by the "Wiki Titles" query based on rankings from the Joint corpus query.  ... 
dblp:conf/tac/SchoneGLLOCDPUM09 fatcat:gys5psypsrawliwzcd3t46ndae

Neural Information Retrieval: A Literature Review [article]

Ye Zhang, Md Mustafizur Rahman, Alex Braylan, Brandon Dang, Heng-Lu Chang, Henna Kim, Quinten McNamara, Aaron Angert, Edward Banner, Vivek Khetan, Tyler McDonnell, An Thanh Nguyen (+3 others)
2017 arXiv   pre-print
While deep NNs have yet to achieve the same level of success in IR as seen in other areas, the recent surge of interest and work in NNs for IR suggest that this state of affairs may be quickly changing  ...  A recent "third wave" of Neural Network (NN) approaches now delivers state-of-the-art performance in many machine learning tasks, spanning speech recognition, computer vision, and natural language processing  ...  engineering. 5.4 Community Question Answering (CQA) Suggu et al. (2016) propose a Deep Feature Fusion Network (DFFN) to exploit both hand-crafted features (HCF) and deep learning based systems for Answer  ... 
arXiv:1611.06792v3 fatcat:i2eqfj5l25epjcytgvifta4y4i

Learning to Enrich Query Representation with Pseudo-Relevance Feedback for Cross-lingual Retrieval

Ramraj Chandradevan, Eugene Yang, Mahsa Yarmohammadi, Eugene Agichtein
2022 Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval  
CCS CONCEPTS • Information systems → Retrieval models and ranking.  ...  However, pseudorelevance feedback (PRF), a family of techniques for improving ranking using the contents of top initially retrieved items, has not been explored with neural CLIR retrieval models.  ...  In this weighting scheme, the models prone to semantically irrelevant documents appear on top ranks.  ... 
doi:10.1145/3477495.3532013 fatcat:uee56yexcrc75cmdypw3liffom

A Hybrid Neural Network BERT-Cap Based on Pre-Trained Language Model and Capsule Network for User Intent Classification

Hai Liu, Yuanxia Liu, Leung-Pun Wong, Lap-Kei Lee, Tianyong Hao, Zhile Yang
2020 Complexity  
User intent classification is a vital component of a question-answering system or a task-based dialogue system.  ...  To better identify user intents, this paper proposes a BERT-Cap hybrid neural network model with focal loss for user intent classification to capture user intents in dialogue.  ...  Attention-based BiGRU-CNN [16] model was proposed for Chinese question classification based on the Fudan University Chinese question dataset.  ... 
doi:10.1155/2020/8858852 fatcat:b5fgjme4ojam5neq3tswtt2z4i

A Survey of Natural Language Generation [article]

Chenhe Dong, Yinghui Li, Haifan Gong, Miaoxin Chen, Junxin Li, Ying Shen, Min Yang
2021 arXiv   pre-print
This paper offers a comprehensive review of the research on Natural Language Generation (NLG) over the past two decades, especially in relation to data-to-text generation and text-to-text generation deep  ...  This survey aims to (a) give the latest synthesis of deep learning research on the NLG core tasks, as well as the architectures adopted in the field; (b) detail meticulously and comprehensively various  ...  [113] present a text expansion method for service recommendation system.  ... 
arXiv:2112.11739v1 fatcat:ygrpp6f25ja4vfbhcr5ycfpxhy
« Previous Showing results 1 — 15 out of 3,893 results