SRASS - A Semantic Relevance Axiom Selection System
نویسندگان
چکیده
This paper describes the design, implementation, and testing of a system for selecting necessary axioms from a large set also containing superfluous axioms, to obtain a proof of a conjecture. The selection is determined by semantics of the axioms and conjecture, ordered heuristically by a syntactic relevance measure. The system is able to solve many problems that cannot be solved alone by the underlying conventional automated reasoning system.
منابع مشابه
A Survey of Axiom Selection as a Machine Learning Problem
Automatic theorem provers struggle to discharge proof obligations of interactive theorem provers. This is partly due to the large number of background facts that are passed to the automatic provers as axioms. Axiom selection algorithms predict the relevance of facts, thereby helping to reduce the search space of automatic provers. This paper presents an introduction to axiom selection as a mach...
متن کاملSemiautomatic Image Retrieval Using the High Level Semantic Labels
Content-based image retrieval and text-based image retrieval are two fundamental approaches in the field of image retrieval. The challenges related to each of these approaches, guide the researchers to use combining approaches and semi-automatic retrieval using the user interaction in the retrieval cycle. Hence, in this paper, an image retrieval system is introduced that provided two kind of qu...
متن کاملPresentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures
Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...
متن کاملPresentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures
Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...
متن کاملAxiomatic approach to feature subset selection basedon
In this paper an axiomatic characterisation of feature subset selection is presented. Two axioms are presented: suuciency axiom | preservation of learning information, and necessity axiom | minimising encoding length. The suuciency axiom concerns the existing dataset and is derived based on the following understanding: any selected feature subset should be able to describe the training dataset ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007