Digital texts in many languages have examples of missing or misused diacritics which makes it hard for natural language processing applications to disambiguate the meaning words. Therefore, restoration is a crucial step languages. In this study we approach problem as bidirectional transformation diacritical letters and their ASCII counterparts, rather than unidirectional diacritic restoration. ...

A massive volume of unstructured data in the form comments, opinions, and other sorts is generated real-time with growth web 2.0. Due to nature data, building an accurate predictive model for sentiment analysis remains a challenging task. While various DNN architectures have been applied encouraging results, they suffer from high dimensional feature space consider features equally. State-of-the...

Information Retrieval (IR) models based on vector spaces have been investigated for a long time. Nevertheless, they have recently attracted further research interest beyond the classical statistical view of vectors and matrices. Moreover, “context” has been recognized as a crucial component of IR systems. As the way context affects IR systems is very complex, a principled approach to modeling a...

Context-awareness is the ability of computing systems to acquire and reason about the situational context and adapt application accordingly. Context-aware system start with gathering of raw, low-level contextual data, interpret the raw contextual data into high-level interpreted context, reason the interpreted context to derive implications and adapt the application behavior on the basis of the...

The behavior of pervasive applications depend not only on their internal state and user interactions but also on contexts sensed during their execution. In this work, we present a collaborative context-aware service platform based on hybrid context management model (enhanced CoCA). It performs reasoning and decisions based on context data, context semantics, and related rules and policies. Such...

Context-aware, multi-channel Web applications are more and more gaining consensus from both content providers and consumers, but very few proposals exist for their conceptual modeling. This paper illustrates a conceptual framework that provides modeling facilities for context-aware, multi-channel Web applications; it also shows how high-level modeling constructs can drive the application develo...

This paper presents a context-aware mobile shopping recommender system. A critique-based baseline recommender system is enhanced by the integration of context conditions like weather, time, temperature and the user’s company. These context conditions are embedded into the recommendation algorithm via preand post-filtering. A nearest neighbor algorithm, using the concept of an average selection ...

This article illustrates the vivid research field of hybrid and context-aware recommender systems. Moreover, two own approaches to deal with context-awareness in recommender systems, are described in detail.

Feature modeling is an approach to represent commonalities and variabilities among products of a product line. Context-aware applications use context information to provide relevant services and information for their users. One of the challenges to build a context-aware product line is to develop mechanisms to incorporate context information and adaptation knowledge in a feature model. This pap...

Ubiquitous Web systems have to deal with varying context information in order to support context awareness. Accomplishing this requirement necessitates gathering, processing and representing that information, so that it can be used for adapting Web applications. In this paper we propose a mechanism for modeling dynamically changing context information like user’s device capabilities and locatio...