Software Product Line (SPL) engineering promotes the systematic and large-scale reuse of design and implementation artifacts. Feature models are one of the main artefact of SPLE approach which essentially characterize the similar and variant functional and operational specifications of the product family. Given the complexity of the variabilities represented by feature models, it is often hard ...

In this paper we analyze the performances of a feature-based and two semantic-based text summarization algorithms on a new Turkish corpus. The feature-based algorithm uses the statistical analysis of paragraphs, sentences, words and formal clues found in documents, whereas the two semanticbased algorithms employ Latent Semantic Analysis (LSA) approach which enables the selection of the most imp...

Background Multiple sclerosis (MS) commonly includes anomia and other communicative deficits that affect participation quality of life. Anomia treatment in MS is currently unexplored. Owing to the degenerative nature MS, compensatory might be preferable restorative treatment. Semantic feature analysis (SFA) has been reported have a effect aphasia traumatic brain injury, it can also used as word...

This paper presents a new image feature that is based on a semantic-level perspective in order to bridge the semantic gap between low-level features of images and high-level concepts of human perception. In this work, low-level image features are first quantized into a set of visual words, and then we apply probabilistic Latent Semantic Analysis model to automatically analyze what kinds of hidd...

Emotion words have been well used as the most obvious choice as feature in the task of textual emotion recognition and automatic emotion lexicon construction. In this work, we explore features for recognizing word emotion. Based on RenCECps (an annotated emotion corpus) and MaxEnt (Maximum entropy) model, several contextual features and their combination have been experimented. Then PLSA (proba...

In this paper we propose to use advanced classification techniques with shape features for nuclei classification in tissue microarray images of renal cell carcinoma. Our aim is to improve the classification accuracy in distinguishing between healthy and cancerous cells. The approach is inspired by natural language processing. Several features are extracted from the automatically segmented nucle...