As known, to finish this book, you may not need to get it at once in a day. Doing the activities along the day may make you feel so bored. If you try to force reading, you may prefer to do other entertaining activities. But, one of concepts we want you to have this book is that it will not make you feel bored. Feeling bored when reading will be only unless you don't like the book. test and diag...

This paper describes our participation in SemEval-2015 Task 12, and the opinion mining system sentiue. The general idea is that systems must determine the polarity of the sentiment expressed about a certain aspect of a target entity. For slot 1, entity and attribute category detection, our system applies a supervised machine learning classifier, for each label, followed by a selection based on ...

The most important causes of bridge failure are local scour. In this study, laboratory experiments were conducted to investigate the effectiveness of slot as a protection device in reduction of depth of scour at cylindrical piers under clear water flow conditions. The development time of scour depth at the circular pier with and without a slot as a protection device was conducted. The experimen...

3 Slotted-Circus (Formal Definition) 10 3.1 Observational Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2 Required Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2.1 Accepted and Refused Events and Equivalent Traces . . . . . . . . . . . . . 11 3.2.2 Null Slots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...

This paper gives the description of the TGB system submitted to the Aspect Based Sentiment Analysis Task of SemEval-2016 (Task 5). The system is built on linear binary classifiers for aspect category classification (Slot 1), on lexicon-based detection for opinion target expressions extraction (Slot 2), and on linear multi-class classifiers for sentiment polarity detection (Slot 3). We conducted...

This paper describes our system submitted to Aspect Based Sentiment Analysis Task 5 of SemEval-2016. Our system consists of two components: binary classifiers trained using single layer feedforward network for aspect category classification (Slot 1), and sequential labeling classifiers for opinion target extraction (Slot 2). Besides extracting a variety of lexicon features, syntactic features, ...