منابع مشابه
m2n: Translating Models to Natural Language Descriptions
To describe the structure of a system, the UML Class Diagram yields the means-of-choice. Therefor, the Class Diagram provides concepts like class, attribute, operation, association, generalization, aggregation, enumeration, etc. When students are introduced to this diagram, they often have to solve exercises where texts in natural language are given and they have to model the described systems....
متن کاملGenerating Natural Language Descriptions of Ontology Concepts
This paper gives an overview of ongoing work on a system for the generation of NL descriptions of classes defined in OWL ontologies. We present a general structuring approach for such descriptions. Since OWL ontologies do not by default contain the information necessary for lexicalization, lexical information has to be added to the data via annotations. A rulebased mechanism for automatically d...
متن کاملCode Similarity via Natural Language Descriptions
Code similarity is a central challenge in many programming related applications, such as code search, automatic translation, and plagiarism detection. In this work, we reduce the problem of semantic relatedness between code fragments into a problem of semantic relatedness of textual descriptions. Our main idea is that we can use the relationship between code and its textual descriptions as esta...
متن کاملNatural language descriptions for video streams
Digital images and videos collection has increased exponentially in the recent years as more and more data is available in the form of personal photo albums, handheld camera videos, feature films and multilingual broadcast news videos, presenting visual data ranging from unstructured to highly structured. Today video data accounts for 80 percent of all network traffic. There is a need for quali...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ACM Computing Surveys
سال: 2016
ISSN: 0360-0300,1557-7341
DOI: 10.1145/2932710