[PDF] Top 20 Multi Task Learning for Conversational Question Answering over a Large Scale Knowledge Base
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Multi Task Learning for Conversational Question Answering over a Large Scale Knowledge Base
... for knowledge-based question answer (KB- QA) in recent years since it does not rely on hand- crafted features and is easy to adapt across do- ...handle large-scale ...a question, and ... See full document
10
Random Walk Inference and Learning in A Large Scale Knowledge Base
... a large-scale semi-supervised multi- task learning algorithm that couples the training of over 1500 different classifiers and extraction methods (see (Carlson et ...NELL’s ... See full document
11
Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering
... selection task, ...of learning the representations of the question and the answer separately, most recent studies utilize attention mechanisms to learn the interaction information between questions ... See full document
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CFO: Conditional Focused Neural Question Answering with Large scale Knowledge Bases
... a large-scale KB such as Free- base contains billions of triples, b) the huge vari- ety of language — there are multiple aliases for an entity, and numerous ways to compose a question, c) the ... See full document
11
Hybrid Question Answering over Knowledge Base and Free Text
... QA task has evolved into two main streams – QA on unstructured data, and QA on structured ...to large scale structured KBs like DBPedia, Freebase (Unger et ... See full document
11
Toward Data Driven Tutorial Question Answering with Deep Learning Conversational Models
... machine learning tech- niques within tools for programming support and computer science ...student’s knowledge states for programming exercises and found that the model was able to successfully identify ... See full document
11
An End to End Model for Question Answering over Knowledge Base with Cross Attention Combining Global Knowledge
... QA task, we filter out the com- pletely unrelated facts to save ...the large scale of ...a multi-task training ...a question, it will weaken the effectiveness of the attention ... See full document
11
Question Answering over Freebase with Multi Column Convolutional Neural Networks
... questions over a knowledge base is an important and challenging ...conduct question under- standing and/or answer ...introduce multi-column convolu- tional neural networks (MCCNNs) to ... See full document
10
Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases
... Unlike SP-based approaches that usually assume a pre-defined set of lexical triggers or rules, which limit their domains and scalability, IR-based ap- proaches directly retrieve answers from the KB in light of the ... See full document
11
Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering
... a large-scale knowledge ...a large-scale human anno- tated dataset, which contains 108,442 natural lan- guage questions for 1,837 relations sampled from FB2M (Bordes et ...A ... See full document
10
Learning Knowledge Graphs for Question Answering through Conversational Dialog
... a question-answering sys- tem can learn about its domain from conver- sational ...a knowledge graph (KG), and uses the graph to solve ...acquire knowledge for question-answering ... See full document
11
IJCNLP 2017 Task 5: Multi choice Question Answering in Examinations
... a question answering(QA) system which could con- sistently understand and correctly answer general questions about the ...tion Answering in Exams”(MCQA) is a typical question answering ... See full document
7
Proceedings of the Open Knowledge Base and Question Answering Workshop (OKBQA 2016)
... Anietie Andy, Mugizi Rwebangira and Satoshi Sekine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Answer Presentation in Question Answering over Linked Data using ... See full document
12
Document retrieval and question answering in medical documents A large scale corpus challenge
... apply as many tests, approximations and refine- ments, because this is the place where most arti- cles condense the biggest amount of relevant in- formation about the content of the document. Of course finding possible ... See full document
7
Interactive Instance based Evaluation of Knowledge Base Question Answering
... output of each step is re-used in the next one. This approach has been exhibited by the most of the recent works on the KB QA (Berant and Liang, 2014; Reddy et al., 2016; Yih et al., 2015; Peng et al., 2017; Sorokin and ... See full document
6
The Open Framework for Developing Knowledge Base And Question Answering System
... This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (No. R0101-16-0054, WiseKB: Big data based self-evolving knowledge ... See full document
5
The Value of Semantic Parse Labeling for Knowledge Base Question Answering
... graph knowledge base. It searches over potential query graphs for a question, iter- atively growing the query graph by sequentially adding a main topic entity, then adding an in- ferential ... See full document
6
Improving Question Answering over Incomplete KBs with Knowledge Aware Reader
... Knowledge-aware Passage Enhancement To encode the retrieved passages, we use a stan- dard bi-LSTM, which takes several token-level features 5 . With the entity linking annotations in passages, we fuse the entity ... See full document
7
Question Answering Using a Large Text Database: A Machine Learning Approach
... [r] ... See full document
7
Knowledge Based Question Answering
... DEF-WORD A/C SENSE AIRCRAFT SENSE AIR-CONDITIONER DEF-WOED EAT SENSE [EAT ACTOR NIL OBJECT NIL TO *INSIDEI PLACE ~STOMACN~ PART NIL] EXPECTATIONS [ IF IN-ACT-SPOT #ANI}~TE THEN SLOTS TO [r] ... See full document
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