Exploring the Impact of Single-Character Attacks in Federated Learning Language Classification: Introducing the Novel Single-Character Strike

Federated learning (FL) is a privacy preserving machine learning approach which allows a machine learning model to be trained in a distributed fashion without ever sharing user data. Due to the large amount of valuable text and voice data stored on end-user devices, this approach works particularly well for natural language processing (NLP)...

Cities for citizens! Public value spheres for understanding conflicts in urban planning

Identifying the diverse and often competing values of citizens, and resolving the consequent public value conflicts, are of significant importance for inclusive and integrated urban development. Scholars have highlighted that relational, value-laden urban space gives rise to many diverse conflicts that vary both spatially and temporally....

Augmenting Ridership Data with Social Media Data to Analyse the Long-term Effect of COVID-19 on Public Transport

COVID-19 significantly influenced travel behaviours and public attitudes towards public transport. Various studies have illustrated complicated factors related to long-term travel behaviour, indicating difficulty in understanding and predicting post-pandemic long-term travel behaviour via traditional methods. In these complex circumstances,...

Supporting Electronic Mental Health with Artificial Intelligence: Thought Record Analysis and Guidance

This thesis investigates how artificial intelligence can support e-mental health for depression, i.e. the delivery of treatment and prevention interventions for depression using technology. E-mental health for depression is a promising means for bridging the treatment gap since it addresses many of the barriers that prevent people in need of...

Complex Knowledge Base Question Answering: A Survey

Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Early studies mainly focused on answering simple questions over KBs and achieved great success. However, their performances on complex questions are still far from satisfactory. Therefore, in recent years, researchers propose a large number of novel...

Toward Linguistic Recognition of Generalized Anxiety Disorder

<b>Background</b>: Generalized anxiety disorder (GAD) refers to extreme, uncontrollable, and persistent worry and anxiety. The disorder is known to affect the social functioning and well-being of millions of people, but despite its prevalence and burden to society, it has proven difficult to identify unique behavioral markers. Interestingly, the...

HyEnA: A Hybrid Method for Extracting Arguments from Opinions

The key arguments underlying a large and noisy set of opinions help understand the opinions quickly and accurately. Fully automated methods can extract arguments but (1) require large labeled datasets and (2) work well for known viewpoints, but not for novel points of view. We propose HyEnA, a hybrid (human + AI) method for extracting...

The Relation Between Words and Definitions in Combined Word-Sentence Space

Methods for learning vector space representations of words have yielded spaces which contain semantic and syntactic regularities. These regularities mean that vector arithmetic operations in the latent space represent meaningful and interpretable relations between words. These word vectors have been so successful in capturing such relations, as...

Designing Depression Screening Chatbots

Advances in voice recognition, natural language processing, and artificial intelligence have led to the increasing availability and use of conversational agents (chatbots) in different settings. Chatbots are systems that mimic human dialogue interaction through text or voice. This paper describes a series of design considerations for...

Predictive Maintenance for Aircraft Systems: Using textual elements as covariates

Unplanned maintenance is a costly factor in aircraft operations. Predictive Maintenance aims at reducing the surprise effect of unplanned maintenance and thereby its associated cost. A variety of statistical models are used to estimate the remaining life, as well as sensors to gauge component condition. The application to statistical models of...

Estimating popularity by sentiment and polarization classification on social media

Mass processing of social media posts has been brought to scientists' attention during the last decade. The massive growth of online social networks, like Twitter and Facebook, have created a need for determining peoples' opinions and moods through these means. This thesis constitutes a research on measuring users' sentiment upon a particular...

Speech-based automatic closed caption alignment

In the Netherlands, four million people watch television programs with closed captions because they are hearing impaired or non-native speakers. Closed captions contain Dutch speech transcriptions and non-speech sound descriptions and are displayed as subtitles. Due to government obligation, the number of television programs that must be closed...

Reasoning about Emotions: An affective natural language processing environment, using lexical relations to measure activation and evaluation, and extracting semantics from natural language

In the field of textual affect sensing many methods have been proposed. These methods vary from keyword spotting techniques, lexical affinity, statistical natural language processing and hand-crafted models. Based on a large scale survey, two profounding theories have been selected for investigation. The first is the proposed work of (Kamps &...

Parallel parsing

This topic of this thesis is parallel parsing using context-free grammars and attribute grammars. The first parts concentrates on slow and fast parallelism of the parsing and recognition process using double dotted items. The second part describe the maximum derivation length of acyclic grammars, the decoration of parses, and a raking algorithm...