Search results for "semanttinen web"

An introduction to knowledge computing

2014

This paper deals with the challenges related to self-management and evolution of massive knowledge collections. We can assume that a self-managed knowledge graph needs a kind of a hybrid of: an explicit declarative self-knowledge (as knowledge about own properties and capabilities) and an explicit procedural self-knowledge (as knowledge on how to utilize own properties and the capabilities for the self-management).We offer an extension to a traditional RDF model of describing knowledge graphs according to the Semantic Web standards so that it will also allow to a knowledge entity to autonomously perform or query from remote services different computational executions needed. We also introdu…

CitySearcher: A City Search Engine For Interests

2017

We introduce CitySearcher, a vertical search engine that searches for cities when queried for an interest. Generally in search engines, utilization of semantics between words is favorable for performance improvement. Even though ambiguous query words have multiple semantic meanings, search engines can return diversified results to satisfy different users' information needs. But for CitySearcher, mismatched semantic relationships can lead to extremely unsatisfactory results. For example, the city Sale would incorrectly rank high for the interest shopping because of semantic interpretations of the words. Thus in our system, the main challenge is to eliminate the mismatched semantic relationsh…

Adaptive semantic web based environment for web resources

2008

Tulevaisuuden kaikkialle ulottuvassa internetissä tietojärjestelmät kommunikoivat paitsi käyttäjien kanssa, myös toisten sovellusten ja instrumentoitujen laitteiden kanssa. Tämän dynaamisen ja heterogeenisen digitaalisen ympäristön hallinnoimiseksi ja hyödyntämiseksi käyttämiemme laitteiden tulisi olla nykyistä proaktiivisempia ja tiedon tulisi olla kuvattu nykyistä kontekstitietoisemmalla tavalla.Lisäksi tulevaisuuden verkon resurssit tulisi kyetä kuvaamaan semanttisesti, jotta eri resurssit voidaan löytää ja sovittaa yhteen automaattisesti. Tämä mahdollistaa myös päätelmien tekemisen järjestelmien tiedoista sekä monimutkaisen kokonaisuuden komponenttien käyttäytymisen ohjaamisen helpommin…

Bridging data mining and semantic web

2016

Nowadays Semantic Web is widely adopted standard of knowledge representation. Hence, knowledge engineers are applying sophisticated methods to capture, discover and represent knowledge in Semantic Web form. Studies show that, to represent knowledge in Semantic Web standard, data mining techniques such as Decision Trees, Association Rules, etc., play an important role. These techniques are implemented in publicly available Data Mining tools. These tools represent knowledge discovered in human readable format and some tools use Predictive Model Markup language (PMML). PMML is an XML based model for data mining model representation that fails to address the representation of the semantics of t…

Graph-based exploration and clustering analysis of semantic spaces

2019

Abstract The goal of this study is to demonstrate how network science and graph theory tools and concepts can be effectively used for exploring and comparing semantic spaces of word embeddings and lexical databases. Specifically, we construct semantic networks based on word2vec representation of words, which is “learnt” from large text corpora (Google news, Amazon reviews), and “human built” word networks derived from the well-known lexical databases: WordNet and Moby Thesaurus. We compare “global” (e.g., degrees, distances, clustering coefficients) and “local” (e.g., most central nodes and community-type dense clusters) characteristics of considered networks. Our observations suggest that …

RDF-tietomalli toimintaprosessin tiedonhallinnan tukena : esimerkkinä suomalainen lainsäädäntöprosessi

2004

Semanttinen muunnos

2008

Dynamic aspects of industrial middleware architectures

2011

Taming big knowledge evolution

2016

Information and its derived knowledge are not static. Instead, information is changing over time and our understanding of it evolves with our ability and willingness to consume the information. When compared to humans, current computer systems seem very limited in their ability to really understand the meaning of things. On the other hand, they are very powerful when it comes down to performing exact computations. One aspect which sets humans apart from machines when trying to understand the world is that we will often make mistakes, forget information, or choose what to focus on. To put this in another perspective, it seems like humans can behave somehow more randomly and still outperform …

Global RDF Vector Space Embeddings

2017

Vector space embeddings have been shown to perform well when using RDF data in data mining and machine learning tasks. Existing approaches, such as RDF2Vec, use local information, i.e., they rely on local sequences generated for nodes in the RDF graph. For word embeddings, global techniques, such as GloVe, have been proposed as an alternative. In this paper, we show how the idea of global embeddings can be transferred to RDF embeddings, and show that the results are competitive with traditional local techniques like RDF2Vec. peerReviewed