[PDF] Top 20 Open Domain Voice Activated Question Answering
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Open Domain Voice Activated Question Answering
... ????????? ??? ???????????????????????? ?"!#?$?%?'&)(+*,?' ? ?/???0?1?, 324??56???,7 8?9 ?;?94<=9?>@9?A?9?BDCFE?G?H?I?JK9 MLONDPF;'N3Q%9 R,SUT G?V?WYX S HZW\[?] ^?[`X T%a W S Vcbedgf S H?d S h H?fji S[.] ... See full document
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Natural Language Generation at Scale: A Case Study for Open Domain Question Answering
... to open-domain ...of open-domain QA pairs from interactions between real-world users and a conversational ...for open-domain QA poses its own challenges compared to task-oriented ... See full document
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Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text
... Open Domain Question Answering (QA) is evolving from complex pipelined systems to end-to-end deep neural ...a question-specific subgraph containing text and KB entities and ... See full document
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PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text
... be interpreted as identifying an entity based on a relationship and related entity, plus additional re- strictions described in text, and it is unclear how to extend such approaches to multi-hop questions. GRAFT-Net (Sun ... See full document
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HAS-QA: Hierarchical Answer Spans Model for Open-Domain Question Answering
... RC models typically have two components: context en- coder and answer decoder. Context encoder is used to ob- tain the embeddings of questions, paragraphs and their in- teractions. Most of recent works are based on the ... See full document
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Evaluation of baseline information retrieval for Polish open-domain Question Answering system
... The a@n of the baseline IR system (Solr) con- figuration ranges from 26% for n = 1 to 87% for n = 200 top documents considered. Our queries consisted of base forms of all question words ex- cept words from a ... See full document
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Open domain Factoid Question Answering via Knowledge Graph Search
... Knowledge graphs contain large amounts of factual information about entities (i.e., well-known places, people and things) and their attributes such as place of birth or profession. Large knowledge graphs gen- erally ... See full document
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Question Answering in the Biomedical Domain
... precise question- specific answers (Pudaruth et ...the domain to evolve from shallow keyword matching to contextual and semantic retrieval sys- tems (Kadam et ...the open- domain (Soares and ... See full document
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Similarity Based Language Model Construction for Voice Activated Open Domain Question Answering
... an open domain voice-activated QA system and our speech recognition module must recognize relatively short, domain independent ...ing domain adaptation method and distri- ... See full document
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The Role of Lexico Semantic Feedback in Open Domain Textual Question Answering
... of question Q221: “Who killed Martin Luther King ?”, by considering the synonym of killer, the noun assassin, the Q&A system retrieved paragraphs with the correct ...the question Q206: “How far is the ... See full document
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Learning Strategies for Open Domain Natural Language Question Answering
... We divided the Remedia corpus into a set of 55 tests used for development, and 60 tests used to evaluate our model, employing the same partition scheme as followed by the prior work mentioned above. With five questions ... See full document
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A Comparative Study of Open Domain and Opinion Question Answering Systems for Factual and Opinionated Queries
... the question and of the extracted answer snippet, using a Support Vector Machines (SVM) classifier trained on the MPQA corpus [6], English NTCIR 2 data and rules based on the subjectivity lexicon ...the ... See full document
5
Simple yet Effective Bridge Reasoning for Open Domain Multi Hop Question Answering
... the systems according to their usages of BERT. Among all the results without BERT, our approach shows a huge advantage and is about 10% higher in terms of both EM and F1 compared to the cur- rent known best system w/o ... See full document
5
Neural Domain Adaptation for Biomedical Question Answering
... Factoid question answering (QA) has re- cently benefited from the development of deep learning (DL) ...large open-domain dataset (SQuAD, source) to a biomedical dataset (BioASQ, target) by ... See full document
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Domain agnostic Question Answering with Adversarial Training
... We implement our model based on the Hugging- Face’s open-source BERT implementation 1 in Py- torch (Paszke et al., 2017). The performance of the baseline in our experiment differs from the of- ficial baseline of ... See full document
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Leveraging Linguistic Structure For Open Domain Information Extraction
... by open domain information extraction (open IE) systems are useful for question answering, infer- ence, and other IE ...state-of-the-art open IE system on the end-to-end TAC-KBP ... See full document
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Paraphrase Driven Learning for Open Question Answering
... construct question answering systems from data (Zelle and Mooney, 1996; Popescu et ...small domain-specific databases like GeoQuery (Tang and Mooney, 2001) or subsets of Freebase (Cai and Yates, ... See full document
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Multi passage BERT: A Globally Normalized BERT Model for Open domain Question Answering
... Passage ranker reranks all retrieved passages, and selects a list of high-quality passages for the multi-passage BERT model. We implement the passage ranker as another BERT model, which is similar to multi-passage BERT ... See full document
5
Real Time Open Domain Question Answering with Dense Sparse Phrase Index
... Model details For the dense vector, we adopt the same setup from Section 6.1 except that we train with no-answer questions (Section 5.1) and an increased batch size of 18. For the sparse vec- tor of each phrase, we use ... See full document
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Open Domain Why Question Answering with Adversarial Learning to Encode Answer Texts
... why- question answering (why-QA) that uses an ad- versarial learning ...supervised open-domain QA (DS-QA) method on pub- licly available English datasets, even though the target task is not a ... See full document
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