This paper describes a system for classifying semantic relations among nominals, as in SemEval task 4. This system uses a corpus of 2,500 compounds annotated with WordNet senses and covering 139 different semantic relations. Given a set of nominal pairs for training, as provided in the SemEval task 4 training data, this system constructs for each training pair a set of features made up of relat...

Named Entity Recognition is a main task in the NLP area that has yielded multiple web-based natural language processors gaining popularity in the Semantic Web community for extracting knowledge from web data. These processors are generally located as pipelines, using dedicated APIs and various taxonomy for extracting, classifying and disambiguating named entities. In this paper, we address the ...

This preface offers a conceptual framework for putting in context the extensive work that has been done in areas related to semantic similarity measuring, approximate semantic methods, document clustering and grouping, and many others that we call generically “Quantitative Semantics”. We present some of the most relevant works in these areas, classifying them so that a kind of map emerges, allo...

In this paper, we introduce IDECSE a new integrated approach for composite services engineering which is based on Semantic Web and Data Mining. IDECSE considers semantics in all the composition steps: user query, semantic classification of services in the registry, composing services, and verifying the composition process. By considering semantics for describing, discovering, composing, and mon...

The translation of traffic flow data into images for the purposes classification in machine learning tasks has been extensively explored recent years. However, method a significant impact on success such attempts. In 2019, called DeepInsight was developed to translate genetic information images. It then adopted 2021 purpose translating network images, allowing retention semantic about relations...

In query-by-semantic-example image retrieval, images are ranked by similarity of semantic descriptors. These descriptors are obtained by classifying each image with respect to a pre-defined vocabulary of semantic concepts. In this work, we consider the problem of improving the accuracy of semantic descriptors through cross-modal regularization, based on auxiliary text. A cross-modal regularizer...

Since the huge database of patent documents is continuously increasing, the issue of classifying, updating and retrieving patent documents turned into an acute necessity. Therefore, we investigate the efficiency of applying Latent Semantic Indexing, an automatic indexing method of information retrieval, to some classes of patent documents from the United States Patent Classification System. We ...

For planning grasps and other object manipulation actions in complex environments, 3D semantic information becomes crucial. This paper focuses on the application of recent 3D Time-of-Flight (ToF) cameras in the context of semantic scene analysis. For being able to acquire semantic information from ToF camera data, we a) pre-process the data including outlier removal, filtering and phase unwrapp...