Recent methods for learning similarity between images have presented impressive results in the problem of pair matching (same/notsame classification) of face images. In this paper we explore how well this performance carries over to the related task of multi-option face identification, specifically on the Labeled Faces in the Wild (LFW) image set. In addition, we seek to compare the performance...

What are the “cognitive after-effects” of making a similarity judgement? What, cognitively, is left behind and what effect might these residues have on subsequent processing? In this paper, we probe for such after-effects using a visual search task, performed after a task in which pictures of real-world objects were compared. So, target objects were first presented in a comparison task (e.g., r...

What are the “cognitive after-effects” of making a similarity judgement? What, cognitively, is left behind and what effect might these residues have on subsequent processing? In this paper, we probe for such after-effects using a visual search task, performed after a task in which pictures of real-world objects were compared. So, target objects were first presented in a comparison task (e.g., r...

We present a fuzzy similarity approach to solve a text categorization problem. The effectiveness of various fuzzy conjunction and disjunction operators used in fuzzy similarity formula and several document representations were evaluated using test sets from three text document collections. Based on empirical results obtained from using these collections, a special case of the fuzzy similarity f...

Up to now, work on semantic relations has focused on relation classification: recognizing whether a given instance (a word pair such as virus:flu) belongs to a specific relation class (such as CAUSE:EFFECT). However, instances of a single relation class may still have significant variability in how characteristic they are of that class. We present a new SemEval task based on identifying the deg...

s In grid computing, the goals of task scheduling is to achieve high system optimization performance while matching multi-dimension Quiality of Service(QoS) requirement of applications. Considering of the autonomous, heterogeneous and distributed feature of the grid system, in this paper, we propose a flexible task scheduling algorithm for grid computing after researching on the existing QoS Gu...

The final goal of Interpretable Semantic Textual Similarity (iSTS) is to build systems that explain which are the differences and commonalities between two sentences. The task adds an explanatory level on top of STS, formalized as an alignment between the chunks in the two input sentences, indicating the relation and similarity score of each alignment. The task provides train and test data on t...