State-of-the-art statistical approaches to the Coreference Resolution task rely on sophisticated modeling, but very few (10-20) simple features. In this paper we propose to extend the standard feature set substantially, incorporating more linguistic knowledge. To investigate the usability of linguistically motivated features, we evaluate our system for a variety of machine learners on the stand...

CLaC-CORE, an exhaustive feature combination system ranked 4th among 34 teams in the Semantic Textual Similarity shared task STS 2013. Using a core set of 11 lexical features of the most basic kind, it uses a support vector regressor which uses a combination of these lexical features to train a model for predicting similarity between sentences in a two phase method, which in turn uses all combi...

Interactive apps are commonly used to support the acquisition of foundational skills. Yet little is known about how pedagogical features such affect learning outcomes, attainment and motivation—particularly when deployed in lower-income contexts, where educational gains most needed. In this study, we analyse which app effective supporting literacy numeracy We compare five developed for Global L...

Systems designed with persuasive software features can influence users to adopt attitudes and/or behaviours that contribute better health outcomes. Studies on Coronary Heart Disease (CHD) interventions have shown how they be used support lifestyle changes. Meta-analytic reviews of randomised controlled trials (RCTs) are needed appraise, summarise, and show their effects health. To this end, we ...

This year, we participated in TRECVID 2010 content-based copy detection task. In this notebook paper we will describe our work in details. Different from last year when we just used SURF (speeded up robust feature) as visual feature, this year we employed a combination of four different features for our rough detection process: global SURF, center SURR, global color correlogram and center corre...