Searched for: +
(1 - 20 of 39)

Pages

List view
Grid view
document
Bezemer, P.R. (author)
Customers interested in buying a product, can search on the internet for reviews about that product. For many products, an enormous amount of information and opinions is available. Customers gets overwhelmed by this information and systems are needed to filter out the essential information. In this research, a model is developed to automatically...
master thesis 2012
document
Khoshnevis, H. (author)
This master thesis is about the sentiment analysis of the societal theme documents and categorizing them in positive or negative groups. The application of this thesis can be widely used in review blogs, public polls and etc. In this study, we have compared different feature sets as well as different classifiers on datasets of opinionated texts...
master thesis 2012
document
Fragkeskos, Kyriakos (author)
With the growing number of scientific publications, the concept<br/>of navigating effectively and searching for domain specific information<br/>is rather significant and highly important for the scientific<br/>community [2]. For instance, to search by topics, research methods,<br/>used datasets, or scientific objectives. Such deep meta-data...
master thesis 2017
document
Ercan, Selman (author)
This thesis project worked towards extending the interactive capabilities of the RoboTutor Nao, by enabling it to answers natural language questions about topics such as computers, robots and the Nao itself. The main questions we focused on were 1) what a system for answering questions in Dutch and intended for elementary school age children...
master thesis 2017
document
Valle Torre, Manuel (author)
In this thesis, we focus on database query processing for so-called experience items, i.e., items commonly encountered in E-Commerce systems such as books, games or movies which are better described by their perceived subjective consumption experience, or Perceptual Features, than by factual meta-data normally used in SQL-style queries. To...
master thesis 2018
document
Kolthof, Daan (author)
In several machine learning problems, a relatively small subproblem is present in which combinations of (negating) objects or structures result in a negation or otherwise other classification compared to when these (negating) objects are not present. To be more specific, a variant of the XOR problem is present in a small amount of objects in...
master thesis 2018
document
Harting, Tom (author)
Open Relation Extraction (ORE) aims to find arbitrary relation tuples between entities in unstructured texts. Even though recent research efforts yield state-of-the-art results for the ORE task by utilizing neural network based models, these works are solely focused on the English language. Methods were proposed to tackle the ORE task for...
master thesis 2019
document
Miglani, Shivam (author)
Automated Planning (AP) is a key component of Artificial General Intelligence and has been successfully employed in applications ranging from scheduling observations of Hubble Space Telescope to generating dialogue agents. A significant bottleneck for its widespread adoption is acquiring accurate domain models which formally encode the planning...
master thesis 2019
document
Manousogiannis, Manolis (author)
Online social networks have revolutionized the way people interact with each other nowadays. Users often share their experiences in various health - related topics like disease symptoms, drug treatments and other medical related issues in order to discuss with other patients dealing with similar conditions. During the production of a new drug,...
master thesis 2019
document
Rovers, Tim (author)
This master thesis explores to what degree information about a company's commitment to privacy can be extracted from a privacy statement. To do this, firstly a new database of more than 1500 privacy statements is created using Amazon Mechanical Turk. Next, 72 different aspects related to privacy of the statements are enumerated by using natural...
master thesis 2019
document
Salmi, Salim (author)
STUDY OBJECTIVE: Suicide crisis chat counsellors work in an environment which de- mands high emotional and cognitive awareness. A shared opinion among counsellors is that as the chat conversation turns more difficult it takes longer and more effort to come up with a response. Supportive technology might resolve this ”writer’s block” by giving...
master thesis 2019
document
Schmahl, Katja (author)
Large text corpora used for creating word embeddings (vectors which represent word meanings) often contain a stereotypical gender bias. This unwanted bias is then also present in the word embeddings and in downstream applications in the field of natural language processing. To prevent and reduce this, more knowledge about the gender bias is...
bachelor thesis 2020
document
Raijmakers, Thijs (author)
Word embeddings are useful for various applications, such as sentiment classification (Tang et al., 2014), word translation (Xing, Wang, Liu, &amp; Lin, 2015) and résumé parsing (Nasser, Sreejith, &amp; Irshad, 2018). Previous research has determined that word embeddings contain gender bias, which can be problematic in certain applications such...
bachelor thesis 2020
document
Happel, David (author)
Using transcripts of the TV-series FRIENDS, this paper explores the problem of predicting the location in which a sentence was said. The research focuses on using feature extraction on the sentences, and training a logistic regression model on those features. Specifically looking at the differences in performance between using ELMo and TF-IDF...
bachelor thesis 2020
document
Chen, Dina (author)
Text classification has a wide range of usage such as extracting the sentiment out of a product review, analyzing the topic of a document and spam detection. In this research, the text classification task is to predict from which TV-show a given line is. The skip-gram model, originally used to train the Word2Vec sentence embeddings [Mikolov et...
bachelor thesis 2020
document
Keukeleire, Pia (author)
In recent years many new text generation models have been developed while evaluation of text generation remains a considerable challenge.  Currently, the only metric that is able to fully capture the quality of a generated text is human evaluation, which is expensive and time consuming. One of the most used intrinsic...
bachelor thesis 2020
document
van Tussenbroek, Thomas (author)
Authorship identification is often applied to large documents, but less so to short, everyday sentences. The ability of identifying who said a short line could provide help to chatbots or personal assistants. This research compares performance of TF-IDF and fastText when identifying authorship of short sentences, by applying these feature...
bachelor thesis 2020
document
Kumar, Paras (author)
With the rapid growth of unstructured data across different mediums, it exposes new challenges for its analysis. To overcome this, data processing pipelines are designed with the help of different tools and technologies for the analysis of data at different stages. One of the applications which we find useful for our company is the creation of...
master thesis 2020
document
Kaptein, Lionel (author)
Many grand challenges like climate change or health security cannot be solved by only the policymakers. Support and expertise of citizens is needed to solve these challenges (Gerton &amp; Mitchell, 2019). Due to the demand for public participation, Participatory Value Evaluation (PVE) fulfils the needs of involving many participants in a...
master thesis 2020
document
Wang, Zina (author)
Relation extraction has been considered as one of the most popular topics nowadays, thanks for its common application in knowledge graph, machine reading and other artificial intelligence sub-field. However, this field has long been suffered from data hunger. Annotating large high-quality datasets for relation extraction is troublesome and time...
master thesis 2020
Searched for: +
(1 - 20 of 39)

Pages

List view
Grid view