Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Jendoubi, Siwar"'
Named Entity Recognition (NER) is a challenging and widely studied task that involves detecting and typing entities in text. So far,NER still approaches entity typing as a task of classification into universal classes (e.g. date, person, or location)
Externí odkaz:
http://arxiv.org/abs/2302.10314
Publikováno v:
In Array September 2023 19
Autor:
Jendoubi, Siwar, Martin, Arnaud
The Viral Marketing is a relatively new form of marketing that exploits social networks to promote a brand, a product, etc. The idea behind it is to find a set of influencers on the network that can trigger a large cascade of propagation and adoption
Externí odkaz:
http://arxiv.org/abs/1907.05028
Autor:
Jendoubi, Siwar, Martin, Arnaud
The influence maximization is the problem of finding a set of social network users, called influencers, that can trigger a large cascade of propagation. Influencers are very beneficial to make a marketing campaign goes viral through social networks f
Externí odkaz:
http://arxiv.org/abs/1706.10188
Social messages classification is a research domain that has attracted the attention of many researchers in these last years. Indeed, the social message is different from ordinary text because it has some special characteristics like its shortness. T
Externí odkaz:
http://arxiv.org/abs/1701.07756
Influence maximization is the problem of selecting a set of influential users in the social network. Those users could adopt the product and trigger a large cascade of adoptions through the " word of mouth " effect. In this paper, we propose two evid
Externí odkaz:
http://arxiv.org/abs/1701.05751
Publikováno v:
FLINS, Aug 2016, Roubaix, France. pp.168 - 174, 2016
In this paper, we propose a new data based model for influence maximization in online social networks. We use the theory of belief functions to overcome the data imperfection problem. Besides, the proposed model searches to detect influencer users th
Externí odkaz:
http://arxiv.org/abs/1610.06340
Publikováno v:
Belief 2014, Sep 2014, Oxford, United Kingdom. pp.284 - 293
Hidden Markov Models (HMMs) are learning methods for pattern recognition. The probabilistic HMMs have been one of the most used techniques based on the Bayesian model. First-order probabilistic HMMs were adapted to the theory of belief functions such
Externí odkaz:
http://arxiv.org/abs/1501.05613
Publikováno v:
International Conference on Modeling, Simulation and Applied Optimization (ICMSAO), Apr 2013, Hammamet, Tunisia. pp.1 - 6
Speech Recognition searches to predict the spoken words automatically. These systems are known to be very expensive because of using several pre-recorded hours of speech. Hence, building a model that minimizes the cost of the recognizer will be very
Externí odkaz:
http://arxiv.org/abs/1501.05530
Publikováno v:
International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), Jul 2014, Montpellier, France. pp.66 - 75
Nowadays, social networks such as Twitter, Facebook and LinkedIn become increasingly popular. In fact, they introduced new habits, new ways of communication and they collect every day several information that have different sources. Most existing res
Externí odkaz:
http://arxiv.org/abs/1501.05426