TY - GEN
T1 - Automatic tagging of texts with contextual factors using knowledge concepts
AU - Prasath, Rajendra
AU - O'Reilly, Philip
AU - Duane, Aidan
PY - 2013
Y1 - 2013
N2 - We present a method to perform automatic tagging of contextual factors associated with mobile payments data. Users specify a short description about the contextual factors interesting to them. The proposed system characterizes these factors and generates the knowledge concepts, similar to [1,2], but with the help of corpus statistics. These knowledge concepts describe the factors in terms of multi-faceted information search. Secondly, given a query, the underlying retrieval system retrieves top k texts pertaining to user information needs. Then based on the similarity between each of the knowledge concepts and the best matching texts, the context matching score is computed. Then the ranked sequence of contextual tags are assigned to the each retrieved text. The experimental results show that the proposed approach characterizes the context from user specified factors and performs the contextual tagging of the retrieved texts in a better way.
AB - We present a method to perform automatic tagging of contextual factors associated with mobile payments data. Users specify a short description about the contextual factors interesting to them. The proposed system characterizes these factors and generates the knowledge concepts, similar to [1,2], but with the help of corpus statistics. These knowledge concepts describe the factors in terms of multi-faceted information search. Secondly, given a query, the underlying retrieval system retrieves top k texts pertaining to user information needs. Then based on the similarity between each of the knowledge concepts and the best matching texts, the context matching score is computed. Then the ranked sequence of contextual tags are assigned to the each retrieved text. The experimental results show that the proposed approach characterizes the context from user specified factors and performs the contextual tagging of the retrieved texts in a better way.
KW - Contextual Tagging
KW - Knowledge Concepts
KW - Learning from Data
KW - Mobile Payments
UR - http://www.scopus.com/inward/record.url?scp=84893357215&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-03844-5_67
DO - 10.1007/978-3-319-03844-5_67
M3 - Conference contribution
AN - SCOPUS:84893357215
SN - 9783319038438
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 687
EP - 694
BT - Mining Intelligence and Knowledge Exploration - First International Conference, MIKE 2013, Proceedings
T2 - 1st International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2013
Y2 - 18 December 2013 through 20 December 2013
ER -