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Content Provider | ACM Digital Library |
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Author | Rothlauf, Franz Pfeiffer, Jella Schunk, Daniel |
Abstract | In search tasks, for example when individuals search for the best price of a product, individuals are confronted in sequential steps with different situations and they have to decide whether to continue or stop searching. The decision behavior of individuals in such search tasks is described by a search strategy.This paper presents a new approach of finding high-quality search strategies by using genetic algorithms (GAs). Only the structure of the search strategies and the basic building blocks (price thresholds and price patterns) that can be used for the search strategies are pre-specified. It is the purpose of the GA to construct search strategies that well describe human search behavior. The search strategies found by the GA are able to predict human behavior in search tasks better than traditional search strategies from the literature which are usually based on theoretical assumptions about human behavior in search tasks. Furthermore, the found search strategies are reasonable in the sense that they can be well interpreted, and generally that means they describe the search behavior of a larger group of individuals and allow some kind of categorization and classification.The results of this study open a new perspective for future research in developing behavioral strategies. Instead of deriving search strategies from theoretical assumptions about human behavior, researchers can directly analyze human behavior in search tasks and find appropriate and high-quality search strategies. These can be used for gaining new insights into the motivation behind human search and for developing new theoretical models about human search behavior. |
Starting Page | 2021 |
Ending Page | 2028 |
Page Count | 8 |
File Format | |
ISBN | 1595930108 |
DOI | 10.1145/1068009.1068346 |
Language | English |
Publisher | Association for Computing Machinery (ACM) |
Publisher Date | 2005-06-25 |
Publisher Place | New York |
Access Restriction | Subscribed |
Subject Keyword | Search strategy Genetic algorithms Human decision behavior |
Content Type | Text |
Resource Type | Article |
National Digital Library of India (NDLI) is a virtual repository of learning resources which is not just a repository with search/browse facilities but provides a host of services for the learner community. It is sponsored and mentored by Ministry of Education, Government of India, through its National Mission on Education through Information and Communication Technology (NMEICT). Filtered and federated searching is employed to facilitate focused searching so that learners can find the right resource with least effort and in minimum time. NDLI provides user group-specific services such as Examination Preparatory for School and College students and job aspirants. Services for Researchers and general learners are also provided. NDLI is designed to hold content of any language and provides interface support for 10 most widely used Indian languages. It is built to provide support for all academic levels including researchers and life-long learners, all disciplines, all popular forms of access devices and differently-abled learners. It is designed to enable people to learn and prepare from best practices from all over the world and to facilitate researchers to perform inter-linked exploration from multiple sources. It is developed, operated and maintained from Indian Institute of Technology Kharagpur.
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Ministry of Education, through its National Mission on Education through Information and Communication Technology (NMEICT), has sponsored and funded the National Digital Library of India (NDLI) project.
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