TY - GEN
T1 - Evaluating Social Media Information Usage in Ranking the Web
AU - Moursi, Ahmed
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10
Y1 - 2015/10
N2 - Information retrieval is a critical issue for everyone online. Searching for information happens all the time. To better retrieve our needs from the web, it's logical to leverage data generated by users via Web 2.0 (web of interaction). Users' actions-such as tagging a page, liking, sharing or other kinds of interaction-are used in this paper to better enhance information retrieval. The work presented in this paper used a dataset from Open Directory Project (ODP) to test the promising use of social services for better ranking of web results. We propose a framework to process social info and use it in the indexing and ranking processes. The proposed framework retrieves data from different kinds of social info (social bookmarking, social news, social network, discovery engines). Raw data is parsed into fields and significant values are either inserted into the index or used in the ranking process. Mean Average Precision (MAP) is used to evaluate results. Results are promising for using social tagging services such as Delicious. An initial assessment of the usage of other social services-for instance Facebook and so on-reveals that their data are not good enough to improve ranking of webpages.
AB - Information retrieval is a critical issue for everyone online. Searching for information happens all the time. To better retrieve our needs from the web, it's logical to leverage data generated by users via Web 2.0 (web of interaction). Users' actions-such as tagging a page, liking, sharing or other kinds of interaction-are used in this paper to better enhance information retrieval. The work presented in this paper used a dataset from Open Directory Project (ODP) to test the promising use of social services for better ranking of web results. We propose a framework to process social info and use it in the indexing and ranking processes. The proposed framework retrieves data from different kinds of social info (social bookmarking, social news, social network, discovery engines). Raw data is parsed into fields and significant values are either inserted into the index or used in the ranking process. Mean Average Precision (MAP) is used to evaluate results. Results are promising for using social tagging services such as Delicious. An initial assessment of the usage of other social services-for instance Facebook and so on-reveals that their data are not good enough to improve ranking of webpages.
KW - Information Retrieval
KW - Information Retrieval Model
KW - Rank Aggregation
KW - Social Info.
KW - Social networks
UR - https://ieeexplore.ieee.org/document/9513452
U2 - 10.1109/ICCTA37466.2015.9513452
DO - 10.1109/ICCTA37466.2015.9513452
M3 - Conference Publication
T3 - 25th International Conference on Computer Theory and Applications, ICCTA 2015 - Proceedings
SP - 84
EP - 90
BT - Proceedings of the 25th International Conference on Computer Theory and Applications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th International Conference on Computer Theory and Applications, ICCTA 2015
Y2 - 24 October 2015 through 26 October 2015
ER -