A CP-ABE Scheme for Multi-user Queries in IoT

2022 ◽  
pp. 619-626
Author(s):  
Fanglin An ◽  
Yin Zhang ◽  
Yi Yue ◽  
Jun Ye
Keyword(s):  
User Queries

The Rapid Development of User Interfaces: Experience with the Wizard of OZ Method

1985 ◽  
Vol 29 (5) ◽  
pp. 470-474 ◽  
Author(s):  
Paul Green ◽  
Lisa Wei-Haas
Keyword(s):  
Personal Computer ◽  
User Interfaces ◽  
Rapid Development ◽  
User Interaction ◽  
Wizard Of Oz ◽  
Iterative Development ◽  
The Subject ◽  
Two Machines ◽  
User Queries

The Wizard of Oz technique is an efficient way to examine user interaction with computers and facilitate rapid iterative development of dialog wording and logic. The technique requires two machines linked together, one for the subject and one for the experimenter. In this implementation the experimenter (the “Wizard”), pretending to be a computer, types in complete replies to user queries or presses function keys to which common messages have been assigned (e.g., Fl=“Help is not available”). The software automatically records the dialog and its timing. This paper provides a detailed description of the first implementation of the Oz paradigm for the IBM Personal Computer. It also includes application guidelines, information which is currently missing from the literature.

Mining User Queries with Markov Chains: Application to Online Image Retrieval

2013 ◽  
Vol 25 (2) ◽  
pp. 433-447 ◽  
Author(s):  
K. A. Raftopoulos ◽  
K. S. Ntalianis ◽  
D. D. Sourlas ◽  
S. D. Kollias
Keyword(s):  
Markov Chains ◽  
Image Retrieval ◽  
User Queries

Application of Genetic Algorithm and Back Propagation Neural Network for Effective Personalize Web Search-Based on Clustered Query Sessions

2016 ◽  
Vol 7 (1) ◽  
pp. 33-49 ◽  
Author(s):  
Suruchi Chawla
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Web Search ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Information Need ◽  
Data Set ◽  
User Query ◽  
User Queries

In this paper novel method is proposed using hybrid of Genetic Algorithm (GA) and Back Propagation (BP) Artificial Neural Network (ANN) for learning of classification of user queries to cluster for effective Personalized Web Search. The GA- BP ANN has been trained offline for classification of input queries and user query session profiles to a specific cluster based on clustered web query sessions. Thus during online web search, trained GA –BP ANN is used for classification of new user queries to a cluster and the selected cluster is used for web page recommendations. This process of classification and recommendations continues till search is effectively personalized to the information need of the user. Experiment was conducted on the data set of web user query sessions to evaluate the effectiveness of Personalized Web Search using GA optimized BP ANN and the results confirm the improvement in the precision of search results.

Ex Ante Evaluations of Alternate Data Structures for End User Queries

2004 ◽  
Vol 15 (4) ◽  
pp. 45-70 ◽  
Author(s):  
Paul L. Bowen ◽  
Fiona H. Rohde ◽  
Jay Basford
Keyword(s):  
Data Structures ◽  
End User ◽  
Ex Ante ◽  
User Queries

SINA: Semantic Interpretation of User Queries for Question Answering on Interlinked Data

2015 ◽  
Author(s):  
Saeedeh Shekarpour ◽  
Edgard Marx ◽  
Axel-Cyrille Ngonga Ngomo ◽  
SSren Auer
Keyword(s):  
Question Answering ◽  
Semantic Interpretation ◽  
User Queries
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