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Word co-occurrence measures co-occurring strength between words in texts. Most of the previous measures use a pre-decided context window to define co-occurrence of words. This size is decided from experience, and it is fixed during the whole process of measure. However, this is not ideal because appropriate window size can be different even in two adjacent sentences of a text. This paper provides...
The Smart Grid is a paradigm shift towards a bidirectional energy and communication system relying on rich information exchange among all involved actors. Based on the experience of the participation in the CEN-CENELEC-ETSI Smart Grid Coordination Group (SG-CG) report creation1 for the EU-Mandate 490 "European Smart Grid Standardization" [1], the EU-funded research project "Open System...
Event detection using webcast text is an important function for providing event based video segmenting services of sport videos. In this paper, an approach of webcast event clustering for sport video event annotation is proposed. In our approach, one of unsupervised learning algorithms, called pLSA (probabilistic latent semantic analysis), is used to classify event types. To decide an appropriate...
In the Web of data, entities are described by interlinked data rather than documents on the Web. In this work, we focus on entity resolution in the Web of data, i.e., identifying descriptions that refer to the same real-world entity. To reduce the required number of pairwise comparisons, methods for entity resolution perform blocking as a pre-processing step. A blocking technique places similar entity...
Blocks-based programming environments offer an alternative program representation to textual source code that simplifies the considerations of syntax for novices. This position paper raises the question of whether additional affordances related to transparency of data, transparency of semantics, and liveness of execution can be consistently added to these environments to obtain some significant advantages...
This paper describes a rule-based sentiment analysis algorithm for polarity classification of financial news articles. The system utilizes a prior polarity lexicon to classify the financial news articles into positive or negative. Sentiment composition rules are used to determine the polarity of each sentence in the news article, while the Positivity/Negativity ratio (P/N ratio) is used to calculate...
Conceptual modeling has been considered a key activity in enterprise architecture and information systems engineering, and comprises the use of diagrammatic languages for communication, understanding and problem solving regarding a universe of discourse. The effectiveness of a modeling language for the aforementioned tasks is strongly related to the languages domain appropriateness, i.e., To the language's...
The assessment of emergent global behaviors of self-organizing applications is an important task to accomplish before employing such systems in real scenarios, yet their intrinsic complexity make this activity still challenging. In this paper we present a logic language used to verify graph-based global properties of self-organizing systems at run-time. The logic language extends a chemical-based...
To form Linked Sensor Data, we can generate linkages among the sensor network data described by semantic information and relevant resources in a Linked Open Data cloud, which can make efficient use of sensor network data. Based on the analysis of existing interlinking methods of Linked Data and Linked Sensor Data publishing systems, according to the property characteristics of sensor network data...
To form Linked Sensor Data, we can generate linkages among the sensor network data described by semantic information and relevant resources in a Linked Open Data cloud, which can make efficient use of sensor network data. Based on the analysis of existing interlinking methods of Linked Data and Linked Sensor Data publishing systems, according to the property characteristics of sensor network data...
Wyner's soft-covering lemma is a valuable tool for achievability proofs of information theoretic security, resolvability, channel synthesis, and source coding. The result herein sharpens the claim of soft-covering by moving away from an expected value analysis. Instead, a random codebook is shown to achieve the soft-covering phenomenon with high probability. The probability of failure is doubly-exponentially...
The exposure of location information in location-based services (LBS) raises users' privacy concerns. Recent research reveals that in LBSs users concern more about the activities that they have performed than the places that they have visited. In this paper, we propose a new attack with which the adversary can accurately infer users' activities. Compared to existing attacks, our attack provides the...
In this paper we propose a method for producing a citation summary of research articles that concentrates on the context of articles which cite the given article. Parameters for citation summary are selected in such a way that, this citation summary can be used to evaluate a qualitative citation index for the research articles. Considering some factors such as, semantic similarity between the citing...
Our unsupervised Search Results Clustering (SRC) system partitions into clusters the top-n results returned by a search engine. We present the results of experiments with our SRC system that performs incremental clustering on document titles and snippets only and does not use external resources, yet which outperforms the best performers to date on the SemEval-2013 Task 11 gold standard. We include...
In this paper, we propose a novel approach for reader-emotion categorization using word embedding learned from neural networks and an SVM classifier. The primary objective of such word embedding methods involves learning continuous distributed vector representations of words through neural networks. It can capture semantic context and syntactic cues, and subsequently be used to infer similarity measures...
A machine translation system converts text from a natural language to other while abiding to the syntax and semantics of the latter. The area of interest here is a Rule Based machine translation system that translates text from English to Malayalam using transfer approach. The system is designed to translate sentences from cricket domain related articles. The purpose behind making the system domain...
Traffic congestion is still a crucial issue because it has a huge impact from the waste of time, the fuel to air pollution. Search information on traffic conditions have been widely available such as through Twitter and the website of CCTV, but the rapid development of online information services resulted in the lack of time to read the complete information. By utilizing the Twitter data, then created...
We present a novel scheme of sentence transformation for Indonesian medical question generation (ImeQG) system by utilizing effectively documents for information navigation. Through the ImeQG proposed method, we conducted a general procedure of dependency analysis for extract verbs and relevant phrases to generate natural sentences by applying transformation rules. For this purpose, we defined some...
Extracting reading interests from a user's reading history is a significant issue of personalized text recommendation. Most previous text recommendation methods only distinguish the interested class from uninterested class, which essentially presumes there is only one angle of reading interests for a user. However a user may have multiple angles of reading interests. Different angles of reading interests...
Adaptive Hypermedia Environments are a suitable means for developing personalized educational content that can respond to the needs of heterogeneous cohorts. These resources are increasingly built upon the Semantic Web, powered by the development and deployment of ontologies. After experimenting the automatic creation of domain ontologies from educational reference books and their use within semantic...
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