Face (sociological concept)

About: Face (sociological concept) is a research topic. Over the lifetime, 5171 publications have been published within this topic receiving 96109 citations. The topic is also known as: Lose face & Face (sociological concept).

Data mining and compression : where to apply it and what are the effects?

Abstract: In data mining it is important for any transforms made to training data to be replicated on evaluation or deployment data. If they is not, the model may perform poorly or be unable to accept the input. Lossy data compression has other considerations, however, for example it may not be known whether or not lossy compression will be applied to deployment data, or if a variable compression ratio is to be used. Furthermore, lossy data compression typically reduces noise, which may not affect or even improve model performances, and performing feature selection on lossy data may find better features than selecting from the original data. In this paper, we investigate the effects of selecting features, learning, and making predictions from data that has been compressed using lossy transforms. Using vehicle telemetry data, we determine where in the data mining methodology lossy compression is detrimental or beneficial, and how it should be compressed. We also propose a specialised feature selection approach that considers predictive performance alongside compressibility, measured by compressing them either individually or in a single concatenated stream

Gandhipedia: A one-stop AI-enabled portal for browsing Gandhian literature, life-events and his social network

Abstract: We introduce an AI-enabled portal that presents an excellent visualization of Mahatma Gandhi's life events by constructing temporal and spatial social networks from the Gandhian literature. Applying an ensemble of methods drawn from NLTK, Polyglot and Spacy we extract the key persons and places that find mentions in Gandhi's written works. We visualize these entities and connections between them based on co-mentions within the same time frame as networks in an interactive web portal. The nodes in the network, when clicked, fire search queries about the entity and all the information about the entity presented in the corresponding book from which the network is constructed, are retrieved and presented back on the portal. Overall, this system can be used as a digital and user-friendly resource to study Gandhian literature.

Controllable Multi-Character Psychology-Oriented Story Generation

Abstract: Story generation, which aims to generate a long and coherent story automatically based on the title or an input sentence, is an important research area in the field of natural language generation. There is relatively little work on story generation with appointed emotions. Most existing works focus on using only one specific emotion to control the generation of a whole story and ignore the emotional changes in the characters in the course of the story. In our work, we aim to design an emotional line for each character that considers multiple emotions common in psychological theories, with the goal of generating stories with richer emotional changes in the characters. To the best of our knowledge, this work is first to focuses on characters' emotional lines in story generation. We present a novel model-based attention mechanism that we call SoCP (Storytelling of multi-Character Psychology). We show that the proposed model can generate stories considering the changes in the psychological state of different characters. To take into account the particularity of the model, in addition to commonly used evaluation indicators(BLEU, ROUGE, etc.), we introduce the accuracy rate of psychological state control as a novel evaluation metric. The new indicator reflects the effect of the model on the psychological state control of story characters. Experiments show that with SoCP, the generated stories follow the psychological state for each character according to both automatic and human evaluations.

Understanding Conditional Compilation Through Integrated Representation of Variability and Source Code

Abstract: The C preprocessor (CPP) is a standard tool for introducing variability into source programs and is often applied either implicitly or explicitly for implementing a Software Product Line (SPL). Despite its practical relevance, CPP has many drawbacks. Because of that it is very difficult to understand the variability implemented using CPP. To facilitate this task we provide an innovative analytics tool which bridges the gap between feature models as more abstract representations of variability and its concrete implementation with the means of CPP. It allows to interactively explore the entities of a source program with respect to the variability realized by conditional compilation. Thus, it simplifies tracing and understanding the effect of enabling or disabling feature flags.