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dc.contributor.authorYan, Fujian
dc.contributor.authorZhang, Yinlong
dc.contributor.authorHe, Hongsheng
dc.date.accessioned2019-01-12T04:54:33Z
dc.date.available2019-01-12T04:54:33Z
dc.date.issued2018
dc.identifier.citationYan F., Zhang Y., He H. (2018) Semantics Comprehension of Entities in Dictionary Corpora for Robot Scene Understanding. In: Ge S. et al. (eds) Social Robotics. ICSR 2018. Lecture Notes in Computer Science, vol 11357. Springer, Chamen_US
dc.identifier.isbn978-303005203-4
dc.identifier.issn0302-9743
dc.identifier.urihttps://doi.org/10.1007/978-3-030-05204-1_35
dc.identifier.urihttp://hdl.handle.net/10057/15756
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractThis paper proposes a method to help robots understand object semantics. The method presented in this paper can enhance robot’s performance and efficiency while working with ambiguous instructions to interact with unfamiliar objects. Specifically, the proposed method can reduce the complexity of assigning the functions, properties or other characteristics for each object which robot may interact within a social environment. The method assists the robot to comprehend the scene based on semantics analysis of the dictionary definition. The proposed semantics comprehension method includes the comprehension of dictionary definitions, the formulation of logic representation, and the generation of natural-language descriptions. The applicability of the approach has been demonstrated. The model performance has been evaluated based on precision, recall, and f-score. Both logic representation formulation results and natural language representation results have been displayed.en_US
dc.language.isoen_USen_US
dc.publisherSpringer Natureen_US
dc.relation.ispartofseriesICSR 2018 10th International Conference on Social Robotics;v.11357
dc.subjectReasoningen_US
dc.subjectRobotic planningen_US
dc.subjectAutonomous robotsen_US
dc.subjectNatural language processen_US
dc.titleSemantics comprehension of entities in dictionary corpora for robot scene understandingen_US
dc.typeConference paperen_US
dc.rights.holder© Springer Nature Switzerland AG 2018en_US


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