Towards Understanding Egyptian Arabic Dialogues

Labelling of user's utterances to understanding his attends which called Dialogue Act (DA) classification, it is considered the key player for dialogue language understanding layer in automatic dialogue systems. In this paper, we proposed a novel approach to user's utterances labeling for Egyptian spontaneous dialogues and Instant Messages using Machine Learning (ML) approach without relying on any special lexicons, cues, or rules. Due to the lack of Egyptian dialect dialogue corpus, the system evaluated by multi-genre corpus includes 4725 utterances for three domains, which are collected and annotated manually from Egyptian call-centers. The system achieves F1 scores of 70. 36% overall domains.Comment: arXiv admin note: substantial text overlap with arXiv:1505.0308

CrowdCE: A Collaboration Model for Crowdsourcing Software with Computing Elements

Today’s crowd computing models are mainly used for handling independent tasks with simplistic collaboration and coordination through business workflows. However, the software development processes are complex, intellectually and organizationally challenging business models. We present a model for software development that addresses key challenges. It is designed for the crowd in the development of a social application. Our model presents an approach to structurally decompose the overall computing element into atomic machine-based computing elements and human-based computing elements such that the elements can complement each other independently and socially by the crowd. We evaluate our approach by developing a business application through crowd work. We compare our model with the traditional software development models. The primary result was completed well for empowering the crowd

Maintaining the search engine freshness using mobile agent

Search engines must keep an up-to-date image to all Web pages and other web resources hosted in web servers in their index and data repositories, to provide better and accurate results to its clients. The crawlers of these search engines have to retrieve the pages continuously to keep the index up-to-date. It is reported in the literature that 40% of the current Internet traffic and bandwidth consumption is due to these crawlers. So we are interested in detecting the significant changes in web pages which reflect effectively in search engine’s index and minimize the network load. In this paper, we suggest a document index based change detection technique and distributed indexing using mobile agents. The experimental results have shown that the proposed system can considerably reduce the network traffic and the computational load on the search engine side and keep its index up-to-date with significant changes

Recognition for old Arabic manuscripts using spatial gray level dependence (SGLD)

Texture analysis forms the basis of object recognition and classification in several domains, one of these domains is historical document manuscripts because the manuscripts hold our culture heritage and also large numbers of undated manuscripts exist. This paper presents results for historical document classification of old Arabic manuscripts using texture analysis and a segmentation free approach. The main objective is to discriminate between historical documents of different writing styles to three different ages: Contemporary (Modern) Age, Ottoman Age and Mamluk Age. This classification depends on a Spatial Gray-level Dependence (SGLD) technique which provides eight distinct texture features for each sample document. We applied Stepwise Discriminant Analysis and Multiple discriminant analysis methods to decrease the dimensionality of features and extract training vector features from samples. To classify historical documents into three main historical age classes the decision tree classification is applied. The system has been tested on 48 Arabic historical manuscripts documents from the Dar Al-Kotob Al-Masria Library. Our results so far yield 95.83% correct classification for the historical Arabic documents