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Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Vector Symbolic Architectures (VSA) are approaches to representing symbols and structured combinations of symbols as high-dimensional vectors. They have applications in machine learning and for understanding information processing in neurobiology. VSAs are typically described in an abstract mathematical form in terms of vectors and operations on vectors. In this work, we show that a machine learning...
We propose a statistical semantic analysis method for Chinese terms. We use words, part-of-speech (POS) tags, word distances, word contexts and the first sememe of a word in HowNet as features to train a Support Vector Machine (SVM) model for analyzing term semantics. The model is used to identify dependencies embedded inside a term. A Conditional Random Field (CRF) model is used afterwards to incorporate...
We have developed a large semi-synthetic, semantically rich dataset, modeled after the medical record of a large medical institution. Using the highly diverse data.gov data repository and a multivariate data augmentation strategy, we can generate arbitrarily large semi-synthetic datasets which can be used to test new algorithms and computational platforms. The construction process and basic data characterization...
This paper presents an approach for semantic word comparison by coupling natural text descriptions with semi-structured knowledge for revealing more precise context information. The goal of the study is to present how popularity of a word's sense can affect semantic relatedness when two words are compared.
SemioTag is an approach towards tagging that utilizes the semiotic sign categories icon, index, and symbol as classification structures to be used by users during the annotation and search of images within social media-oriented repositories. We compared the influence of this approach on the tagging and querying behaviour of users, with respect to usability, efficiency, and user experience, between...
The rate at which biomedical literature is being published is quickly outpacing our ability to effectively leverage this information for evidence-based medicine. While papers are readily searchable through databases such as Pub Med, clinicians are often left with the time-consuming task of finding, assessing, interpreting, and applying this information. Tools that structure evidence from published...
The ability to reason over large scale data and return responsive query results is widely seen as a critical step to achieving the Semantic Web vision. We describe an approach for partitioning OWL Lite datasets and then propose a strategy for parallel reasoning about concept instances and role instances on each partition. The partitions are designed such that each can be reasoned on independently...
We investigate user requirements regarding the interface design for a semantic multimedia search and retrieval based on a prototypical implementation of a search engine for multimedia content on the web. Thus, unlike existing image search engines and video search engines, we are interested in true multimedia content combining different media assets into multimedia documents like PowerPoint presentations...
Detection of human behavior in On-line Social Networks (OSNs) has become more and more important for a wide range of applications, such as security, marketing, parent controls and so on, opening a wide range of novel research areas, which have not been fully addressed yet. In this paper, we present a two-stage method for anomaly detection in humans' behavior while they are using a social network....
Connecting ontological representations and data models is a crucial need in enterprise knowledge management, above all in the case of federated enterprises where corporate ontologies are used to share information coming from different databases. OWL to ERD transformations are a challenging research field in this scenario, due to the loss of expressiveness arising when OWL axioms have to be represented...
The amount of data within the Linking Open Data (LOD) cloud is steadily increasing and resembles a rich source of information. Since Context-aware Services (CAS) can highly benefit from background information, e.g., about the environment of a user, it makes sense to leverage that enormous amount of data already present in the LOD cloud to enhance the quality of these services. Within this work, the...
Cultural heritage resources are huge and heterogeneous. They include highly structured, very unstructured, and semi-structured data or information obtained from both authorized and unauthorized sources and involving multimedia data including text, audio and video data. With the rapid development of the web, more and more cultural heritage organizations use digital methods to record, store and represent...
Ontologies are a vital component of most knowledge-based applications, including semantic web search, intelligent information integration, and natural language processing. In particular, we need effective tools for generating in-depth ontologies that achieve comprehensive converge of specific application domains of interest, while minimizing the time and cost of this process. Therefore we cannot rely...
The amount of the internet video has been growing rapidly in recent years. Efficient video indexing and retrieval, therefore, is becoming an important research and system-design issue. Reliably extracting metadata from video as indexes is one major step toward efficient video management. There are numerous video types, and everyone can define new video types of his own. We believe an open video analysis...
This paper discusses principles for the design of natural language processing (NLP) systems to automatically extract of data from doctor's notes, laboratory results and other medical documents in free-form text. We argue that rather than searching for 'atom units of meaning' in the text and then trying to generalize them into a broader set of documents through increasingly complicated system of rules,...
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