His primary areas of investigation include Natural language processing, Artificial intelligence, Programming language, Program comprehension and Natural language. The Natural language processing study combines topics in areas such as Entropy, Transformation based learning, Semantics and Cluster analysis. His study in the field of Lexical item is also linked to topics like Position.
His Program comprehension research includes elements of Java, Software development, Software construction and Heuristics. The concepts of his Natural language study are interwoven with issues in Software, Info URI scheme and Source code. His work on Software maintenance as part of his general Software study is frequently connected to Contextual advertising, thereby bridging the divide between different branches of science.
K. Vijay-Shanker mainly investigates Artificial intelligence, Natural language processing, Programming language, Information retrieval and Rule-based machine translation. His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning, Set and Biomedical text mining. His Natural language processing study integrates concerns from other disciplines, such as Transformation based learning and Program comprehension.
The Programming language study which covers Natural language that intersects with Source code, Software, Software maintenance, Program analysis and Identifier. His work on Information extraction as part of general Information retrieval research is frequently linked to MEDLINE, bridging the gap between disciplines. His work carried out in the field of Rule-based machine translation brings together such families of science as Theoretical computer science, Tree, Locality, Grammar and Formalism.
Artificial intelligence, Text mining, Relationship extraction, Natural language processing and Information retrieval are his primary areas of study. His study looks at the relationship between Artificial intelligence and topics such as Machine learning, which overlap with Adversarial system. He combines subjects such as Scalability, Computational biology and Pipeline with his study of Text mining.
His primary area of study in Natural language processing is in the field of Natural language. K. Vijay-Shanker has researched Natural language in several fields, including Program comprehension, Software development, Oracle, Identifier and Empirical research. His Information retrieval study combines topics in areas such as Sentence, World Wide Web, Interoperability, Knowledge extraction and Semantics.
K. Vijay-Shanker focuses on Computational biology, Text mining, Information retrieval, Knowledge extraction and Posttranslational modification. His research integrates issues of Relationship extraction and Gene in his study of Text mining. His studies deal with areas such as XML, World Wide Web and Interoperability as well as Information retrieval.
Extramural combines with fields such as Natural language processing and Artificial intelligence in his investigation. As a part of the same scientific family, he mostly works in the field of Natural language processing, focusing on Java and, on occasion, Natural language. His Artificial intelligence study incorporates themes from Programming language, Software and Open source.
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The Convergence of Mildly Context-Sensitive Grammar Formalisms
Aravind Joshi;K. Vijay-Shanker;David Weir.
Towards automatically generating summary comments for Java methods
Giriprasad Sridhara;Emily Hill;Divya Muppaneni;Lori Pollock.
automated software engineering (2010)
CHARACTERIZING STRUCTURAL DESCRIPTIONS PRODUCED BY VARIOUS GRAMMATICAL FORMALISMS
K. Vijay-Shanker;David J. Weir;Aravind K. Joshi.
meeting of the association for computational linguistics (1987)
The equivalence of four extensions of context-free grammars
K. Vijay-Shanker;D. J. Weir.
Theory of Computing Systems / Mathematical Systems Theory (1994)
Automatic generation of natural language summaries for Java classes
Laura Moreno;Jairo Aponte;Giriprasad Sridhara;Andrian Marcus.
international conference on program comprehension (2013)
Using natural language program analysis to locate and understand action-oriented concerns
David Shepherd;Zachary P. Fry;Emily Hill;Lori Pollock.
aspect-oriented software development (2007)
Automatically capturing source code context of NL-queries for software maintenance and reuse
Emily Hill;Lori Pollock;K. Vijay-Shanker.
international conference on software engineering (2009)
Mining source code to automatically split identifiers for software analysis
Eric Enslen;Emily Hill;Lori Pollock;K. Vijay-Shanker.
mining software repositories (2009)
Feature structures based Tree Adjoining Grammars
K. Vijay-Shanker;A. K. Joshi.
international conference on computational linguistics (1988)
Using descriptions of trees in a tree adjoining grammar
Computational Linguistics (1992)
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