scholarly journals Considerations about learning Word2Vec

2021 ◽  
Author(s):  
Giovanni Di Gennaro ◽  
Amedeo Buonanno ◽  
Francesco A. N. Palmieri
Keyword(s):  
Ad Hoc Network ◽  
Ad Hoc ◽  
High Accuracy ◽  
Learning Rate ◽  
Open Questions ◽  
Starting Point ◽  
The Creation ◽  
Occurrence Matrix ◽  
Very High ◽  
Large Diffusion

AbstractDespite the large diffusion and use of embedding generated through Word2Vec, there are still many open questions about the reasons for its results and about its real capabilities. In particular, to our knowledge, no author seems to have analysed in detail how learning may be affected by the various choices of hyperparameters. In this work, we try to shed some light on various issues focusing on a typical dataset. It is shown that the learning rate prevents the exact mapping of the co-occurrence matrix, that Word2Vec is unable to learn syntactic relationships, and that it does not suffer from the problem of overfitting. Furthermore, through the creation of an ad-hoc network, it is also shown how it is possible to improve Word2Vec directly on the analogies, obtaining very high accuracy without damaging the pre-existing embedding. This analogy-enhanced Word2Vec may be convenient in various NLP scenarios, but it is used here as an optimal starting point to evaluate the limits of Word2Vec.

scholarly journals The TanDEM-X Change DEM: the New Temporal DEM of the TanDEM-X Mission

2020 ◽  
Author(s):  
Marie Lachaise ◽  
Markus Bachmann ◽  
Thomas Fritz ◽  
Martin Huber ◽  
Barbara Schweißhelm ◽  
...  
Keyword(s):  
Data Processing ◽  
High Accuracy ◽  
Temporal Separation ◽  
Starting Point ◽  
Acquisition Planning ◽  
Very High

The TanDEM-X mission is acquiring a new dataset to provide a temporally independent DEM, called "TanDEM-X Change DEM". This set of acquisitions taken between 2017 and 2020 has a clear temporal separation to the TanDEM-X global DEM data which were acquired between 2010 and 2015. Therefore, this new DEM aims to enable the characterization of terrain changes. Improvements in the acquisition planning and the data processing were necessary to generate this Change DEM with fewer acquisitions but still very high accuracy. For this, the use of an edited TanDEM-X DEM as a "starting point" for the interferometric processing is mandatory.

scholarly journals Android Malware Classification Using Deep Learning CNN with Co-occurrence Matrix Feature 

2020 ◽  
Vol 31 (1) ◽  
pp. 9-17
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Image Recognition ◽  
High Accuracy ◽  
Experimental Results ◽  
Android Malware ◽  
Malware Classification ◽  
Occurrence Matrix ◽  
Very High

Recently, deep learning has been widely applying to speech and image recognition. Convolutional neural network (CNN) is one of the main categories to do image classifications with very high accuracy. In Android malware classification field, many works have been trying to convert Android malwares into “images” to make them well-matched with the CNN input to take advantage of the CNN model. The performance, however, is not significantly improved because simply converting malwares into images may lack several important features of the malwares. This paper proposes a method for improving the feature set of Android malware classification based on co-concurrence matrix (co-matrix). The co-matrix is established based on a list of raw features extracted from .apk files. The proposed feature can take the advantage of CNN while remaining important features of the Android malwares. Experimental results of CNN model conducted on a very popular Android malware dataset, Drebin, prove the feasibility of our proposed co-matrix feature.

ANALISIS KASUS KANKER LIDAH DALAM KONTEKS ASUHAN KEPERAWATAN DENGAN PENDEKATAN COMFORT THEORY MODEL

2018 ◽  
Vol 12 (02) ◽  
Author(s):  
Dewi Nurviana Suharto
Keyword(s):  
Nursing Care ◽  
Tongue Cancer ◽  
Theory Model ◽  
Breathing Patterns ◽  
Patients With Cancer ◽  
Starting Point ◽  
Squamous Cell Carcinoma Tongue ◽  
Very High ◽  
Carcinoma Tongue ◽  
Comfort Theory

ABSTRACT The prevalence of patients with cancer increase every year. Tongue cancer is a type of malignancy of the tongue, and almost 95% is squamous cell carcinoma. Tongue cancer is a cancer with high progression with bad prognosis so that the mortality rate is very high and often causes discomfort. Comfort is the starting point of various healing that will be achieved by the client. Improvements in client conditions will not be achieved if the need of comfort is not fulfilled. In nursing care the problems that arise in tongue cancer are chronic pain, nutrient imbalance: less than body needs, and ineffective breathing patterns. Analysis of residency practice processes shows that comfort theory can be applied to patients with malignancy cases in nursing care, as it can identify patients' holistic discomfort from the physical, psychospiritual, sociocultural and environmental aspects.Keyword : Comfort Theory, Tongue Cancer

Spontaneous Ad HoC Network Creation Using Distributed Dns

2012 ◽  
Vol 3 (5) ◽  
pp. 207-209
Author(s):  
Nayana K Nayana K ◽  
◽  
Dr.Sangeethaa Sukumaran
Keyword(s):  
Ad Hoc Network ◽  
Ad Hoc

Node Name Routing in Information-Centric Ad-Hoc Network

2017 ◽  
Vol E100.A (2) ◽  
pp. 680-687 ◽  
Author(s):  
Zheng WEN ◽  
Di ZHANG ◽  
Keping YU ◽  
Takuro SATO
Keyword(s):  
Ad Hoc Network ◽  
Ad Hoc
Sign in / Sign up

Export Citation Format

Share Document