Linguistic labels affect inductive generalization; however, the mechanism underlying these effects remains unclear. According to one similarity-based model, SINC (similarity, induction, naming, and categorization), early in development labels are features of objects contributing to the overall similarity of compared entities, with early induction being similarity based. If this is the case, the...

In verbal memory, similarity between items in memory often leads to interference and impaired memory performance. The present study sought to determine whether analogous interference effects would be observed in visual working memory by varying the similarity of the to-be-remembered objects in a color change-detection task. Instead of leading to interference and impaired performance, increased ...

The analysis of moving entities “trajectories” is an important task in different application domains, since it enables the analyst to design, evaluate and optimize navigation spaces. Trajectory clustering is aimed at identifying the objects moving in similar paths and it helps the analysis and obtaining of efficient patterns. Since clustering depends mainly on similarity, the computing similari...

In two studies, we investigated the ability of a variety of structural and temporal measures computed from a web navigation path to predict lostness and task success. The user’s task was to find requested target information on specified websites. The web navigation measures were based on counts of visits to web pages and other statistical properties of the web usage graph (such as compactness, ...

In this paper we describe the detailed information of NLP-NITMZ system on the participation of DPIL shared task at Forum for Information Retrieval Evaluation (FIRE 2016). The main aim of DPIL shared task is to detect paraphrases in Indian Languages. Paraphrase detection is an important part in the field of Information Retrieval, Document Summarization, Question Answering, Plagiarism Detection e...

Chiu (1972) reported that in a categorization task, Chinese children were more likely to categorize objects based on shared relationships, whereas American children were more likely to categorize objects based on similarity. This research examines whether such findings generalize to adults and whether cultural differences would also be observed in the activation of semantic concepts. In Experim...

We present in this paper the systems we participated with in the Semantic Textual Similarity task at SEM 2013. The Semantic Textual Similarity Core task (STS) computes the degree of semantic equivalence between two sentences where the participant systems will be compared to the manual scores, which range from 5 (semantic equivalence) to 0 (no relation). We combined multiple text similarity meas...

Task selection in micro-task markets can be supported by recommender systems to help individuals to find appropriate tasks. Previous work showed that for the selection process of a micro-task the semantic aspects, such as the required action and the comprehensibility, are rated more important than factual aspects, such as the payment or the required completion time. This work gives a foundation...

We describe UMBC’s systems developed for the SemEval 2014 tasks on Multilingual Semantic Textual Similarity (Task 10) and Cross-Level Semantic Similarity (Task 3). Our best submission in the Multilingual task ranked second in both English and Spanish subtasks using an unsupervised approach. Our best systems for Cross-Level task ranked second in Paragraph-Sentence and first in both Sentence-Phra...

We report results obtained by the UoW method in SemEval-2014’s Task 10 – Multilingual Semantic Textual Similarity. We propose to model Semantic Textual Similarity in the context of Multi-task Learning in order to deal with inherent challenges of the task such as unbalanced performance across domains and the lack of training data for some domains (i.e. unknown domains). We show that the Multi-ta...