The Information Search System Using Neural Network and Fuzzy Clustering Based on Mobile Agent

2005 ◽  
pp. 205-214 ◽  
Author(s):  
Jaeseon Ko ◽  
Bobby D. Gerardo ◽  
Jaewan Lee ◽  
Jae-Jeong Hwang
Keyword(s):  
Neural Network ◽  
Fuzzy Clustering ◽  
Mobile Agent ◽  
Information Search ◽  
Search System

Tourism Information Search System Based on Android Mobile Phone

2014 ◽  
Vol 687-691 ◽  
pp. 2728-2731
Author(s):  
Yan Hu
Keyword(s):  
Mobile Phone ◽  
Information Search ◽  
Multimedia Application ◽  
Normal Operation ◽  
Application Software ◽  
Search System ◽  
Google Maps ◽  
Operation System ◽  
Guide System ◽  
Tourism Information

In this paper, a design and an implementation on an intelligent guide system based on Android platform is proposed. The hardware of system is based on ARM platform, and the schematics of its main modules such as power, SDRAM are given. Then Android operation system is transplanted on the ARM platform. On this basis, the application software is developed using Eclipse and Android SDK, and it is consisted of three modules: multimedia application, web maps and recording. The module of multimedia application includes audio, picture and video. Web maps can display Google Maps on the device and achieve positioning. The record module has implemented the several normal operation on a record, such as creating, modifying and displaying.

Semantic Representation of a Geo-Social User Profile for a Personalised Information Retrieval

2021 ◽  
pp. 2150044
Author(s):  
Tahar Rafa ◽  
Samir Kechid
Keyword(s):  
Information Retrieval ◽  
Information Search ◽  
Semantic Representation ◽  
User Profile ◽  
Search Process ◽  
Search System ◽  
User Interactions ◽  
User Interests ◽  
Situational Contexts ◽  
User Query

The user-centred information retrieval needs to introduce semantics into the user modelling for a meaningful representation of user interests. The semantic representation of the user interests helps to improve the identification of the user’s future cognitive needs. In this paper, we present a semantic-based approach for a personalised information retrieval. This approach is based on the design and the exploitation of a user profile to represent the user and his interests. In this user profile, we combine an ontological semantics issued from WordNet ontology, and a personal semantics issued from the different user interactions with the search system and with his social and situational contexts of his previous searches. The personal semantics considers the co-occurrence relations between relevant components of the user profile as semantic links. The user profile is used to improve two important phases of the information search process: (i) expansion of the initial user query and (ii) adaptation of the search results to the user interests.

scholarly journals Understanding collaborative tourism information searching to support online travel planning

2019 ◽  
Vol 43 (3) ◽  
pp. 369-386 ◽  
Author(s):  
Abu Shamim Mohammad Arif ◽  
Jia Tina Du
Keyword(s):  
Information Search ◽  
User Study ◽  
Ease Of Use ◽  
Online Information ◽  
Information Searching ◽  
Search System ◽  
Content Type ◽  
Travel Planning ◽  
Collaborative Search ◽  
Tourism Information

Purpose Collaborative information searching is common for people when planning their group trip. However, little research has explored how tourists collaborate during information search. Existing tourism Web portals or search engines rarely support tourists’ collaborative information search activities. Taking advantage of previous studies of collaborative tourism information search behavior, in the current paper the purpose of this paper is to propose the design of a collaborative search system collaborative tourism information search (ColTIS) to support online information search and travel planning. Design/methodology/approach ColTIS was evaluated and compared with Google Talk-embedded Tripadvisor.com through a user study involving 18 pairs of participants. The data included pre- and post-search questionnaires, web search logs and chat history. For quantitative measurement, statistical analysis was performed using SPSS; for log data and the qualitative feedback from participants, the content analysis was employed. Findings Results suggest that collaborative query formulation, division of search tasks, chatting and results sharing are important means to facilitate tourists’ collaborative search. ColTIS was found to outperform Tripadvisor significantly regarding the ease of use, collaborative support and system usefulness. Originality/value The innovation of the study lies in the development of an integrated real-time collaborative tourism information search system with unique features. These features include collaborative query reformulation, travel planner and automatic result and query sharing that assist multiple people search for holiday information together. For system designers and tourism practitioners, implications are provided.

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