[PDF] Top 20 Semantics based Graph Approach to Complex Question Answering

... We also analyzed errors found in our experiment. The majority of errors were caused by errors from depen- dency parsing, semantic role labeling, or coreference resolution. For instance, verbs are not recognized correctly ... See full document

... applied semantics [4], where the mapping between linguistic objects is carried out by means of semantic inferences at the textual ...input question Q (the text in the TE terminology) and a set of relational ... See full document

... since Question Answering (QA) emerged as an active research field, the community has slowly diversified question types, increased question com- plexity, and refined evaluation metrics - as ... See full document

... proposed approach for the Episodic Memory QA task, we create a new dataset, MemQA, of 100K question and an- swer pairs composed based on synthetic memory graphs that are artificially ...memory ... See full document

... The Human-computer interactive retrieval module consists of entity-relation visualization, relevant illustration and knowledge association. The entity-relation visualization assists common users to view all associated ... See full document

... Given our commitment to the assumption we made i.e. the text to be annotated is well-constructed, it is possible that one sentence in the middle of the text might be related to another in the beginning. In his work, ... See full document

... 8 inevitably omitted, these would need to be restored from some background knowledge text about these omitted entities and the ones presented in Q. Moreover, a logical flow needs to complement that of the Q. The ... See full document

... the question logically follows from the answer using a set of axioms that are automatically extracted from the WordNet ...the question term “age” can be inferred from the atomic formula that corresponds to ... See full document

... a question retrieval framework on the basis of semantic graphs which makes use of an external resource (namely DB- pedia ) as the background knowledge to overcome the prob- lem of the lexical gap between the ... See full document

... over complex connected datasets require the client to enter a complete and all around shaped question, and present the answers as crude arrangements of ...component based punctuation with a full ... See full document

... a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate ...guage question posed by the user and the candidate sentences returned from search ... See full document

... We release a QA data-set ComplexQuestions which contains multi-constraint questions, and propose a novel systematic KBQA method using multi-constraint query graph to answer multi-constraint questions. Experiments ... See full document

... A knowledge graph is a collection of assertions. In an assertion, a source entity is connected to a tar- get entity through a directed and labeled edge. Large knowledge graphs such as Freebase contain billions of ... See full document

... a question answering (QA) ...The question to the QA system is: “Does the described event cause the emotion of ...system based on a deep memory ... See full document

... the approach of using graphs and graph transformations in order to specify the semantics of a dynamic language, we would like to state that we believe that using this approach has proved to be ... See full document

... traditional question answering system can provide users direct answers, the data source is still based on fixed document sets and it cannot satisfy all kinds of need from the ...by question ... See full document

... Purpose Question Answering system, since they are formed by a single ...as complex those questions that are formed by more than one event related by a temporal signal which establishes an order ... See full document

... We established a number of assessor variables. So far, we only have had time to evaluate the effect of a few of these but we present these to give indications of the importance of recording this class of information. ... See full document

... pages about different persons, it is highly possible that they are grouped into one cluster because they share many similar words and phrases. On the other hand, it is difficult to group together a news page and a resume ... See full document

... lattice based CNN model (LCNs) to utilize multi-granularity information inherent in the word lattice while maintaining strong ability to deal with the introduced noisy information for matching based ... See full document