scholarly journals Personalized Search-based Query Rewrite System for Conversational AI

2021 ◽  
Author(s):  
Eunah Cho ◽  
Ziyan Jiang ◽  
Jie Hao ◽  
Zheng Chen ◽  
Saurabh Gupta ◽  
...  
Keyword(s):  
Personalized Search ◽  
Rewrite System

NEURO-FUZZY BASED SEARCH ROBOT FOR SOFTWARE COMPONENTS

1999 ◽  
Vol 08 (02) ◽  
pp. 119-135
Author(s):  
YAU-HWANG KUO ◽  
JANG-PONG HSU ◽  
MONG-FONG HORNG
Keyword(s):  
Retrieval System ◽  
Software Component ◽  
Software Components ◽  
Personalized Search ◽  
Component Retrieval ◽  
Reusable Software ◽  
Major Mechanism ◽  
Fuzzy Models ◽  
Neuro Fuzzy

A personalized search robot is developed as one major mechanism of a personalized software component retrieval system. This search robot automatically finds out the Web servers providing reusable software components, extracts needed software components from servers, classifies the extracted components, and finally establishes their indexing information for local component retrieval in the future. For adaptively tuning the performance of software component extraction and classification, an adaptive thesaurus and an adaptive classifier, realized by neuro-fuzzy models, are embedded in this search robot, and their learning algorithms are also developed. A prototype of the personalized software component retrieval system including the search robot has been implemented to confirm its validity and evaluate the performance. Furthermore, the framework of proposed personalized search robot could be extended to the search and classification of other kinds of Internet documents.

Design of personalized search engine based on user-webpage dynamic model

2013 ◽  
Author(s):  
Jihan Li ◽  
Shanglin Li ◽  
Yingke Zhu ◽  
Bo Xiao
Keyword(s):  
Dynamic Model ◽  
Search Engine ◽  
Personalized Search

scholarly journals OORS: An object-oriented rewrite system

2007 ◽  
Vol 4 (2) ◽  
pp. 2-26
Author(s):  
Gernot Gebhard ◽  
Philipp Lucas
Keyword(s):  
Code Generation ◽  
Graphics Processing Units ◽  
Object Oriented ◽  
Graphics Hardware ◽  
Code Optimization ◽  
Target Architecture ◽  
Rewrite Rules ◽  
Graphics Processing ◽  
Traditional Approaches ◽  
Rewrite System

Retargeting a compiler?s back end to a new architecture is a time-consuming process. This becomes an evident problem in the area of programmable graphics hardware (graphics processing units, GPUs) or embedded processors, where architectural changes are faster than elsewhere. We propose the object-oriented rewrite system OORS to overcome this problem. Using the OORS language, a compiler developer can express the code generation and optimization phase in terms of cost-annotated rewrite rules supporting complex non-linearmatching and replacing patterns. Retargetability is achieved by organizing rules into profiles, one for each supported target architecture. Featuring a rule and profile inheritance mechanism, OORS makes the reuse of existing specifications possible. This is an improvement regarding traditional approaches. Altogether OORS increases the maintainability of the compiler?s back end and thus both decreases the complexity and reduces the effort of the retargeting process. To show the potential of this approach, we have implemented a code generation and a code optimization pattern matcher supporting different target architectures using the OORS language and introduced them in a compiler of a programming language for CPUs and GPUs.

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