The Experts below are selected from a list of 14043 Experts worldwide ranked by ideXlab platform
Hosagrahar Visvesvaraya Jagadish - One of the best experts on this subject based on the ideXlab platform.
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constructing an interactive Natural Language Interface for relational databases
Very Large Data Bases, 2014Co-Authors: Hosagrahar Visvesvaraya JagadishAbstract:Natural Language has been the holy grail of query Interface designers, but has generally been considered too hard to work with, except in limited specific circumstances. In this paper, we describe the architecture of an interactive Natural Language query Interface for relational databases. Through a carefully limited interaction with the user, we are able to correctly interpret complex Natural Language queries, in a generic manner across a range of domains. By these means, a logically complex English Language sentence is correctly translated into a SQL query, which may include aggregation, nesting, and various types of joins, among other things, and can be evaluated against an RDBMS. We have constructed a system, NaLIR (Natural Language Interface for Relational databases), embodying these ideas. Our experimental assessment, through user studies, demonstrates that NaLIR is good enough to be usable in practice: even naive users are able to specify quite complex ad-hoc queries.
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nalir an interactive Natural Language Interface for querying relational databases
International Conference on Management of Data, 2014Co-Authors: Hosagrahar Visvesvaraya JagadishAbstract:In this demo, we present NaLIR, a generic interactive Natural Language Interface for querying relational databases. NaLIR can accept a logically complex English Language sentence as query input. This query is first translated into a SQL query, which may include aggregation, nesting, and various types of joins, among other things, and then evaluated against an RDBMS. In this demonstration, we show that NaLIR, while far from being able to pass the Turing test, is perfectly usable in practice, and able to handle even quite complex queries in a variety of application domains. In addition, we also demonstrate how carefully designed interactive communication can avoid misinterpretation with minimum user burden.
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danalix a domain adaptive Natural Language Interface for querying xml
International Conference on Management of Data, 2007Co-Authors: Ishan Chaudhuri, Huahai Yang, Satinder Singh, Hosagrahar Visvesvaraya JagadishAbstract:We present DaNaLIX, a prototype domain-adaptive Natural Language Interface for querying XML. Our system is an extension of NaLIX, a generic Natural Language Interface for querying XML. While retaining the portability of a purely generic system like NaLIX, DaNaLIX can exploit domain knowledge, whenever available, to its advantage for query translation. More importantly, in DaNaLIX such domain knowledge does not have to be pre-defined; instead it can be automatically obtained from the interactions between a user and the system. In this demonstration, we describe the overall architecture of DaNaLIX. We also demonstrate how a generic system like DaNaLIX can take advantage of domain knowledge to improve its usability and query translation accuracy. In addition, we show DaNaLIX still possesses the portability of a generic system by using data collections from three different domains. Finally, we present how domain knowledge can be obtained through user interactions in an automatic fashion.
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Constructing a Generic Natural Language Interface for an XML Database
Advances in Database Technology - EDBT 2006, 2006Co-Authors: Yunyao Li, Huahai Yang, Hosagrahar Visvesvaraya JagadishAbstract:We describe the construction of a generic Natural Language query Interface to an XML database. Our Interface can accept an arbitrary English sentence as a query, which can be quite complex and include aggregation, nesting, and value joins, among other things. This query is translated, potentially after reformulation, into an XQuery expression. The translation is based on mapping grammatical proximity of Natural Language parsed tokens in the parse tree of the query sentence to proximity of corresponding elements in the XML data to be retrieved. Our experimental assessment, through a user study, demonstrates that this type of Natural Language Interface is good enough to be usable now, with no restrictions on the application domain.
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Nalix:an Interactive Natural Language Interface for Query ing XML, SIGMOD
2005Co-Authors: Huahai Yang, Hosagrahar Visvesvaraya JagadishAbstract:Database query Languages can be intimidating to the nonexpert, leading to the immense recent popularity for keyword based search in spite of its significant limitations. The holy grail has been the development of a Natural Language query Interface. We present NaLIX, a generic interactive Natural Language query Interface to an XML database. Our system can accept an arbitrary English Language sentence as query input, which can include aggregation, nesting, and value joins, among other things. This query is translated, potentially after reformulation, into an XQuery expression that can be evaluated against an XML database. The translation is done through mapping grammatical proximity of Natural Language parsed tokens to proximity of corresponding elements in the result XML. In this demonstration, we show that NaLIX, while far from being able to pass the Turing test, is perfectly usable in practice, and able to handle even quite complex queries in a variety of application domains. In addition, we also demonstrate how carefully designed features in NaLIX facilitate the interactive query process and improve the usability of the Interface. 1
Jerome A Feldman - One of the best experts on this subject based on the ideXlab platform.
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exploiting deep semantics and compositionality of Natural Language for human robot interaction
Intelligent Robots and Systems, 2016Co-Authors: Manfred Eppe, Sean Trott, Jerome A FeldmanAbstract:We are developing a Natural Language Interface for human robot interaction that implements reasoning about deep semantics in Natural Language. To realize the required deep analysis, we employ methods from cognitive linguistics, namely the modular and compositional framework of Embodied Construction Grammar (ECG) [18]. Using ECG, robots are able to solve fine-grained reference resolution problems and other issues related to deep semantics and compositionality of Natural Language. This also includes verbal interaction with humans to clarify commands and queries that are too ambiguous to be executed safely. We implement our NLU framework as a ROS package and present proof-of-concept scenarios with different robots, as well as a survey on the state of the art in knowledge-based Language HRI.
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exploiting deep semantics and compositionality of Natural Language for human robot interaction
arXiv: Artificial Intelligence, 2016Co-Authors: Manfred Eppe, Sean Trott, Jerome A FeldmanAbstract:We develop a Natural Language Interface for human robot interaction that implements reasoning about deep semantics in Natural Language. To realize the required deep analysis, we employ methods from cognitive linguistics, namely the modular and compositional framework of Embodied Construction Grammar (ECG) [Feldman, 2009]. Using ECG, robots are able to solve fine-grained reference resolution problems and other issues related to deep semantics and compositionality of Natural Language. This also includes verbal interaction with humans to clarify commands and queries that are too ambiguous to be executed safely. We implement our NLU framework as a ROS package and present proof-of-concept scenarios with different robots, as well as a survey on the state of the art.
Miguel Toro Bonilla - One of the best experts on this subject based on the ideXlab platform.
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a generic Natural Language Interface for task planning application to a mobile robot
Control Engineering Practice, 2000Co-Authors: Jose Mariano Gonzalez Romano, E F Camacho, Juan Gomez Ortega, Miguel Toro BonillaAbstract:Abstract This paper presents a generic Natural Language Interface that can be applied to the teleoperation of different kinds of complex interactive systems. Through this Interface the operators can ask for simple actions or more complex tasks to be executed by the system. Complex tasks will be decomposed into simpler actions generating a network of actions whose execution will result in the accomplishment of the required task. As a practical application, the system has been applied to the teleoperation of a real mobile robot, allowing the operator to move the robot in a partially structured environment through Natural Language sentences.
Manfred Eppe - One of the best experts on this subject based on the ideXlab platform.
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exploiting deep semantics and compositionality of Natural Language for human robot interaction
Intelligent Robots and Systems, 2016Co-Authors: Manfred Eppe, Sean Trott, Jerome A FeldmanAbstract:We are developing a Natural Language Interface for human robot interaction that implements reasoning about deep semantics in Natural Language. To realize the required deep analysis, we employ methods from cognitive linguistics, namely the modular and compositional framework of Embodied Construction Grammar (ECG) [18]. Using ECG, robots are able to solve fine-grained reference resolution problems and other issues related to deep semantics and compositionality of Natural Language. This also includes verbal interaction with humans to clarify commands and queries that are too ambiguous to be executed safely. We implement our NLU framework as a ROS package and present proof-of-concept scenarios with different robots, as well as a survey on the state of the art in knowledge-based Language HRI.
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exploiting deep semantics and compositionality of Natural Language for human robot interaction
arXiv: Artificial Intelligence, 2016Co-Authors: Manfred Eppe, Sean Trott, Jerome A FeldmanAbstract:We develop a Natural Language Interface for human robot interaction that implements reasoning about deep semantics in Natural Language. To realize the required deep analysis, we employ methods from cognitive linguistics, namely the modular and compositional framework of Embodied Construction Grammar (ECG) [Feldman, 2009]. Using ECG, robots are able to solve fine-grained reference resolution problems and other issues related to deep semantics and compositionality of Natural Language. This also includes verbal interaction with humans to clarify commands and queries that are too ambiguous to be executed safely. We implement our NLU framework as a ROS package and present proof-of-concept scenarios with different robots, as well as a survey on the state of the art.
Traian Rebedea - One of the best experts on this subject based on the ideXlab platform.
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dataset for a neural Natural Language Interface for databases nnlidb
International Joint Conference on Natural Language Processing, 2017Co-Authors: Florin Brad, Radu Cristian Alexandru Iacob, Ionel Alexandru Hosu, Traian RebedeaAbstract:Progress in Natural Language Interfaces to databases (NLIDB) has been slow mainly due to linguistic issues (such as Language ambiguity) and domain portability. Moreover, the lack of a large corpus to be used as a standard benchmark has made data-driven approaches difficult to develop and compare. In this paper, we revisit the problem of NLIDBs and recast it as a sequence translation problem. To this end, we introduce a large dataset extracted from the Stack Exchange Data Explorer website, which can be used for training neural Natural Language Interfaces for databases. We also report encouraging baseline results on a smaller manually annotated test corpus, obtained using an attention-based sequence-to-sequence neural network.
