UMBC ebiquity
2014 June

Archive for June, 2014

TISA Topic Independence Scoring Algorithm

June 23rd, 2014, by Tim Finin, posted in GENERAL

Justin Martineau, Doreen Cheng and Tim Finin, TISA: topic independence scoring algorithm. In Proc. 9th Int. Conf. on Machine Learning and Data Mining (MLDM’13), pp. 555-570, July 2013, Springer-Verlag.

Textual analysis using machine learning is in high demand for a wide range of applications including recommender systems, business intelligence tools, and electronic personal assistants. Some of these applications need to operate over a wide and unpredictable array of topic areas, but current in-domain, domain adaptation, and multi-domain approaches cannot adequately support this need, due to their low accuracy on topic areas that they are not trained for, slow adaptation speed, or high implementation and maintenance costs.

To create a true domain-independent solution, we introduce the Topic Independence Scoring Algorithm (TISA) and demonstrate how to build a domain-independent bag-of-words model for sentiment analysis. This model is the best preforming sentiment model published on the popular 25 category Amazon product reviews dataset. The model is on average 89.6% accurate as measured on 20 held-out test topic areas. This compares very favorably with the 82.28% average accuracy of the 20 baseline in-domain models. Moreover, the TISA model is highly uniformly accurate, with a variance of 5 percentage points, which provides strong assurance that the model will be just as accurate on new topic areas. Consequently, TISAs models are truly domain independent. In other words, they require no changes or human intervention to accurately classify documents in never before seen topic areas.

Ebiquity alumna Lalana Kagal featured for privacy work

June 15th, 2014, by Tim Finin, posted in alumni, Ebiquity, Privacy, Security, Semantic Web

Congratulations to ebiquity alumna Lalana Kagal (Ph.D. 2004) for being featured on MIT’s home page recently for recent work with Ph.D. student Oshani Seneviratne on enabling people to track how their private data is used online. You can read more about their work via this MIT news item and in their paper Enabling Privacy Through Transparency which will be presented next month in the 2014 IEEE Privacy Security and Trust conference.

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