Children's Internet searching on complex problems: performance and process analyses
Journal of the American Society for Information Science - Special issue on user-centered cooperative systems
The measurement of readability: useful information for communicators
ACM Journal of Computer Documentation (JCD)
Design criteria for children's Web portals: the users speak out
Journal of the American Society for Information Science and Technology
Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Support vector machines classification with a very large-scale taxonomy
ACM SIGKDD Explorations Newsletter - Natural language processing and text mining
Detecting online commercial intention (OCI)
Proceedings of the 15th international conference on World Wide Web
Reading level assessment using support vector machines and statistical language models
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Know your neighbors: web spam detection using the web topology
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
The Journal of Machine Learning Research
Web page classification: Features and algorithms
ACM Computing Surveys (CSUR)
Automatic readability assessment for people with intellectual disabilities
ACM SIGACCESS Accessibility and Computing
Refined experts: improving classification in large taxonomies
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Cognitively motivated features for readability assessment
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Importance of HTML structural elements and metadata in automated subject classification
ECDL'05 Proceedings of the 9th European conference on Research and Advanced Technology for Digital Libraries
Personalizing web search results by reading level
Proceedings of the 20th ACM international conference on Information and knowledge management
Detection of news feeds items appropriate for children
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
EmSe: supporting children's information needs within a hospital environment
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Supporting children's web search in school environments
Proceedings of the 4th Information Interaction in Context Symposium
EmSe: initial evaluation of a child-friendly medical search system
Proceedings of the 4th Information Interaction in Context Symposium
Classifying websites into non-topical categories
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
Estimating content concreteness for finding comprehensible documents
Proceedings of the sixth ACM international conference on Web search and data mining
Increasing cheat robustness of crowdsourcing tasks
Information Retrieval
Vertical selection in the information domain of children
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
Copulas for information retrieval
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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Today children interact more and more frequently with information services. Especially in on-line scenarios there is a great amount of content that is not suitable for their age group. Due to the growing importance and ubiquity of the Internet in today's world, denying children any unsupervised Web access is often not possible. This work presents an automatic way of distinguishing web pages for children from those for adults in order to improve child-appropriate web search engine performance. A range of 80 different features based on findings from cognitive sciences and children's psychology are discussed and evaluated. We conducted a large scale user study on the suitability of web sites and give detailed information about the insights gained. Finally a comparison to traditional web classification methods as well as human annotator performance reveals that our automatic classifier can reach a performance close to that of human agreement.