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Wyświetlanie 1-3 z 3
Tytuł:
Statistical proper name recognition in Polish economic texts
Autorzy:
Marcińczuk, M.
Piasecki, M.
Powiązania:
https://bibliotekanauki.pl/articles/206385.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
proper name recognition
named entity recognition
machine learning
hidden Markov model
rule-base approach
dictionary-base approach
Opis:
In the paper we present a Proper Name Recognition algorithm based on the Hidden Markov Model (HMM). Recognition of the Proper Names (PN) is treated as the basis for Named Entity Recognition problem in general. The proposed method is based on combining domain-dependent method based on HMM with domain independent methods based on gazetteers and hand-written rules for recognition and post-processing that capture the general properties of Polish PN structure. A large gazetteer with entries described morphologically was acquired from the web. The HMM re-scoring mechanism was applied as a basis for integration of different knowledge sources in PN recognition. Results of experiments on a domain corpus of Polish stock exchange reports, used for training and testing, are presented. A cross-domain evaluation on two other corpora is also presented. Adaptability of the method was analysed by applying the trained model to two other domain corpora.
Źródło:
Control and Cybernetics; 2011, 40, 2; 393-418
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Machine Use and the Supply Chain Efficiency in the Manufacturing Company
Autorzy:
Wojciechowski, A.
Powiązania:
https://bibliotekanauki.pl/articles/409122.pdf
Data publikacji:
2016
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
Total Productive Maintenance
OEE
hidden machine
availability of inventory
Opis:
The increase of machine utilization in manufacturing companies contributes significantly to improving customer logistics service by ensuring the availability of stocks at the required level. The aim of the article is to present the impact of the improved machine use in the manufacturing plant of the lighting industry on supply chain efficiency. The first part discussed the performance indicators of machine use in the Total Productive Maintenance grasp with suggestions of their improvement. The second part presents the facilitation of the machine use process in the company. It also contains the analysis of the influence of the machine use improvement on shaping the availability of component inventory of the customer.
Źródło:
Research in Logistics & Production; 2016, 6, 2; 165-176
2083-4942
2083-4950
Pojawia się w:
Research in Logistics & Production
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Lifelogging system based on averaged Hidden Markov Models: dangerous activities recognition for caregiver support
Autorzy:
Postawka, A.
Rudy, J.
Powiązania:
https://bibliotekanauki.pl/articles/305668.pdf
Data publikacji:
2018
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
lifelogging
abnormal human activity recognition
machine vision
Microsoft Kinect
Hidden Markov Models
Opis:
In this paper, a prototype lifelogging system for monitoring people with cognitive disabilities and elderly people as well as a method for the automatic detection of dangerous activities are presented. The system allows for the remote monitoring of observed people via an Internet website and respects the privacy of the people by displaying their silhouettes instead of their actual images. The application allows for the viewing of both real-time and historical data. The lifelogging data (skeleton coordinates) needed for posture and activity recognition are acquired using Microsoft Kinect 2.0. Several activities are marked as potentially dangerous and generate alarms sent to caregivers upon detection. Recognition models are developed using Averaged Hidden Markov Models with multiple learning sequences. Action recognition includes methods for dierentiating between normal and potentially dangerous activities (e.g., self-aggressive autistic behavior) using the same motion trajectory. Some activity recognition examples and results are presented.
Źródło:
Computer Science; 2018, 19 (3); 257-278
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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