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Bootstrapping Ontology Evolution with Multimedia Information Extraction [chapter]

Georgios Paliouras, Constantine D. Spyropoulos, George Tsatsaronis
2011 Lecture Notes in Computer Science  
This process involves, on the one hand, the continuous extraction of semantic information from multimedia content in order to populate and enrich the ontologies and, on the other hand, the deployment of  ...  Thus, in addition to annotating multimedia content with semantics, the extracted knowledge is used to expand our understanding of the domain and extract even more useful knowledge.  ...  Driven by domain-specific multimedia ontologies, BOEMIE information extraction systems are able to identify high-level semantic features in image, video, audio and text and fuse these features for improved  ... 
doi:10.1007/978-3-642-20795-2_1 fatcat:rnn442weubdrvhp2bzza6odaca

Crowdsourcing semantic content: A model and two applications

Angelo Di lorio, Alberto Musetti, Silvio Peroni, Fabio Vitali
2010 3rd International Conference on Human System Interaction  
The expressive power and flexibility of OWiki proved to be the right trade-off to deploy the authoring environments for such very different domains, ensuring at the same time editing freedom and semantic  ...  Ontology-driven forms and templates are the key concepts of the system, that allows even inexpert users to create consistent semantic data with little effort.  ...  The authors also recognize endless credit to Silvia Duca and Valentina Bolognini for their previous works about Gaffe.  ... 
doi:10.1109/hsi.2010.5514513 fatcat:62iknjevqzd6bji4frngm6prau

Implicit, Formal and Powerful Semantics in Geoinformation

Gloria Bordogna, Cristiano Fugazza, Paolo Acquaviva d'Aragona, Paola Carrara
2021 ISPRS International Journal of Geo-Information  
to the three distinct forms of semantics.  ...  Then, we illustrate several case studies, following the categorization into implicit, formal, and powerful (i.e., soft) semantics depending on the kind of their input.  ...  Formal and powerful semantics share "Semantics-driven user interfaces/interaction paradigms/...  ... 
doi:10.3390/ijgi10050330 fatcat:tscz7fb6evbhdo7fw4lyf3i4yq

Recent Research Advances on Interactive Machine Learning [article]

Liu Jiang, Shixia Liu, Changjian Chen
2018 arXiv   pre-print
Interactive Machine Learning (IML) is an iterative learning process that tightly couples a human with a machine learner, which is widely used by researchers and practitioners to effectively solve a wide  ...  We conclude the survey with a discussion of open challenges and research opportunities that we believe are inspiring for future work in IML.  ...  (Krueger et al., 2015) present a visual analytics approach for semantic movement analysis. They enrich the geospatial movements with POIs obtained from social media.  ... 
arXiv:1811.04548v1 fatcat:4pihx2imurd2lj7hc524uiyafi

A Review of Text Corpus-Based Tourism Big Data Mining

Qin Li, Shaobo Li, Sen Zhang, Jie Hu, Jianjun Hu
2019 Applied Sciences  
We summarize and discuss different text representation strategies, text-based NLP techniques for topic extraction, text classification, sentiment analysis, and text clustering in the context of tourism  ...  The successes of these techniques have been further boosted by the progress of natural language processing (NLP), machine learning, and deep learning.  ...  , discover semantic relationships between domain concepts [140] , and gradually form large-scale semantic network diagrams, etc.  ... 
doi:10.3390/app9163300 fatcat:chb3pbtj5jgq7fauniomsb22yu

Augmented Natural Language for Generative Sequence Labeling [article]

Ben Athiwaratkun, Cicero Nogueira dos Santos, Jason Krone, Bing Xiang
2020 arXiv   pre-print
We propose a generative framework for joint sequence labeling and sentence-level classification.  ...  Unlike prior discriminative methods, our model naturally incorporates label semantics and shares knowledge across tasks.  ...  For instance, we convert "object type" to "object type" and "AddToPlaylist" to "add to playlist". These rules result in better tokenization and enrich the label semantics.  ... 
arXiv:2009.13272v1 fatcat:4l2wynwy3zbjpnb2qh6fim6mie

Semantic trajectories modeling and analysis

Christine Parent, Nikos Pelekis, Yannis Theodoridis, Zhixian Yan, Stefano Spaccapietra, Chiara Renso, Gennady Andrienko, Natalia Andrienko, Vania Bogorny, Maria Luisa Damiani, Aris Gkoulalas-Divanis, Jose Macedo
2013 ACM Computing Surveys  
trajectories from movement tracks, (ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and (iii) using data mining to analyze semantic trajectories  ...  This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for: (i) constructing  ...  Two machine learning techniques are very popular in this context: clustering and classification.  ... 
doi:10.1145/2501654.2501656 fatcat:g7nr36bop5eslcfmr4z34mvj4i

Semantic trajectories

Zhixian Yan, Dipanjan Chakraborty, Christine Parent, Stefano Spaccapietra, Karl Aberer
2013 ACM Transactions on Intelligent Systems and Technology  
trajectories enriched with segmentations and annotations.  ...  The core contribution of this paper lies in a Semantic Model and a Computation and Annotation Platform for developing a semantic approach that progressively transforms the raw mobility data into semantic  ...  Trajectory Data Enrichment The goal of trajectory data enrichment is to add semantic annotations by using geographic and application domain knowledge.  ... 
doi:10.1145/2483669.2483682 fatcat:ppv7g6kihjattjmf7g6nb3txxy

SUDIR: An Approach of Sensing Urban Text Data from Internet Resources based on Deep Learning

Chaoran Zhou, Jianping Zhao, Chenghao Ren
2020 IEEE Access  
RECOGNIZING URBAN DATA BASED ON BERT-WWM AND BLSTM-CRF SUDIR's urban data recognition model uses the WWM strategy of the CWS concept to construct word embeddings to enrich semantic representation, and  ...  (NU=21310, 9856) for POI-name and POI-address recognition.  ...  For more information, see  ... 
doi:10.1109/access.2020.3040408 fatcat:5cgd4soqprhaxfd64imk7hf22y

Multi-source knowledge fusion: a survey

Xiaojuan Zhao, Yan Jia, Aiping Li, Rong Jiang, Yichen Song
2020 World wide web (Bussum)  
promote the construction of domain knowledge graphs (KGs), and bring enormous social and economic benefits.  ...  On the one hand, the process of multi-source knowledge reasoning can detect conflicts and provide help for knowledge evaluation and verification; on the other hand, the new knowledge acquired by knowledge  ...  as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.  ... 
doi:10.1007/s11280-020-00811-0 fatcat:ef5j2sna6fai7k2455yihrrfuq

Introduction [chapter]

Peter Spyns
2012 Essential Speech and Language Technology for Dutch  
STEVIN advocated an integrated approach: develop text and speech resources and tools, stimulate innovative strategic and application-oriented research, promote embedding of HLT in existing applications  ...  Several calls were issued, and they included three open calls and two calls for tender as well.  ...  author(s) and source are credited.  ... 
doi:10.1007/978-3-642-30910-6_1 dblp:series/tanlp/Spyns13 fatcat:x3hadalrirbvliitkmzj74xtqi

Mobility driven Cloud-Fog-Edge Framework for Location-aware Services: A Comprehensive Review [article]

Shreya Ghosh, Soumya Ghosh
2020 arXiv   pre-print
While cloud paradigm is suitable for the capability of storage and computation, the major bottleneck is network connectivity loss.  ...  Therefore, this chapter discusses the concerns and challenges associated with mobility-driven cloud-fog-edge based framework to provide several location-aware services to the end-users efficiently.  ...  The process of appending such semantic information is defined as semantic enrichment.  ... 
arXiv:2007.04193v1 fatcat:ghxpcgofpraxfhosirzfa7bzhi

POI Mining for Land Use Classification: A Case Study

Renato Andrade, Ana Alves, Carlos Bento
2020 ISPRS International Journal of Geo-Information  
In the last few years, driven by the increased availability of geo-referenced data from social media, embedded sensors, and remote sensing images, various techniques have become popular for land use analysis  ...  Then, based on a systematic state-of-the-art study, we focused on exploring the potential of points of interest (POIs) for land use classification, as one of the most common categories of crowdsourced  ...  HSC is used for LULC and functional zone classification by using data such as remote sensing images, POIs, and road blocks.  ... 
doi:10.3390/ijgi9090493 fatcat:5h4oggosirbpddmtsrlyxqghza

Content-based Music Recommendation: Evolution, State of the Art, and Challenges [article]

Yashar Deldjoo, Markus Schedl, Peter Knees
2021 arXiv   pre-print
The music domain is among the most important ones for adopting recommender systems technology.  ...  In the past years, music recommendation models that leverage collaborative and content data -- which we refer to as content-driven models -- have been replacing pure CF or CB models.  ...  model playlists as Markov chains (MCs) and propose logistic Markov Embeddings (LMEs) to learn the representations of songs for playlist prediction.  ... 
arXiv:2107.11803v1 fatcat:4hz4hqkkmvcapbdr3wvtp2t4iu

User-Generated Content: A Promising Data Source for Urban Informatics [chapter]

Song Gao, Yu Liu, Yuhao Kang, Fan Zhang
2021 The Urban Book Series  
First, we use geotagged social media data, a type of single-sourced UGC, to extract citizen demographics, mobility patterns, and place semantics associated with various urban functional regions.  ...  Drawing on the analyses, we summarize a number of future research areas that call for attention in urban informatics.  ...  Acknowledgements Song Gao would like to thank the support of this research from the Office of the Vice Chancellor for Research and Graduate Education at the University of Wisconsin-Madison with funding  ... 
doi:10.1007/978-981-15-8983-6_28 fatcat:hhigrdxtkfbkpctappf237jy64
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