This paper describes our systems submitted to the Sentence-level and Text-level AspectBased Sentiment Analysis (ABSA) task (i.e., Task 5) in SemEval-2016. The task involves two phases, namely, Aspect Detection phase and Sentiment Polarity Classification phase. We participated in the second phase of both subtasks in laptop and restaurant domains, which focuses on the sentiment analysis based on ...

In this paper we present a novel approach to shape similarity estimation. The target application is content-based indexing and retrieval over large image databases. The technique is based on wavelet decomposition and uses polygon approximation over several scales. This technique uses simple features (aspect ratio, angles, distances from the centroid, distance ratios and relative positions) extr...

This paper describes our systems submitted to the target-dependent sentiment polarity classification subtask in aspect based sentiment analysis (ABSA) task (i.e., Task 12) in SemEval 2015. To settle this problem, we extracted several effective features from three sequential sentences, including sentiment lexicon, linguistic and domain specific features. Then we employed these features to constr...

dimension seep : drip Emphasis enemy : foe Denotational, indirect error : mistake Denotational, fuzzy woods : forest Stylistic, formality pissed : drunk : inebriated Stylistic, force ruin : annihilate Expressed attitude skinny : thin : slim, slender Emotive daddy : dad : father Collocational task : job Selectional pass away : die Subcategorization give : donate 2.3 Dimensions of variation The p...

Floods are one of the most important natural hazards in world and Turkey, depending on their severity formation conditions, they can cause disasters by creating diverse negative impacts sources from effects or human intervention. In this study, flood susceptibility map was prepared conducting analysis Çerçi River Fethiye District Mugla Province, Turkey. While determining River, geologic, geomor...

This study performs a GIS-based landslide susceptibility assessment using convolutional neural network, CNN, in area of the Gorzineh-khil region, northeastern Iran. For this assessment, 15-layered CNN was programmed Python high-level language for mapping. In regard, as far landside triggering factors are concerned, it concluded that geomorphologic/topographic parameters (i.e., slope curvature, ...