Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userCorpus sp{e}cialis{e} et ressource de sp{e}cialit{e}
265
0
0.0
(
0
)
Added by
Bernard Jacquemin
Publication date
2015
fields
Informatics Engineering
and research's language is
English
Authors
Bernard Jacquemin
Ask ChatGPT about the research
No Arabic abstract
Semantic Atlas is a mathematic and statistic model to visualise word senses according to relations between words. The model, that has been applied to proximity relations from a corpus, has shown its ability to distinguish word senses as the corpus contributors comprehend them. We propose to use the model and a specialised corpus in order to create automatically a specialised dictionary relative to the corpus domain. A morpho-syntactic analysis performed on the corpus makes it possible to create the dictionary from syntactic relations between lexical units. The semantic resource can be used to navigate semantically - and not only lexically - through the corpus, to create classical dictionaries or for diachronic studies of the language.
rate research
Read More
We proove some inequalities concerning the product, sup * inf for some elliptic operators of order 2 and 4. Using those inequalities and the concentration phenomena we can describe the asymptotic behavior of those PDE solutions.
We give some remarks on some manifolds K3 surfaces, Complex projective spaces, real projective space and Torus and the classification of two dimensional Riemannian surfaces, Green functions and the Stokes formula. We also, talk about traces of Sobolev spaces, the distance function, the notion of degree and a duality theorem, the variational formulation and conformal map in dimension 2, the metric on the boundary of a Lipschitz domain and polar geodesic coordinates and the Gauss-Bonnet formula and the positive mass theorem in dimension 3 and in the locally conformally flat case. And the Ricci flow. And fields and their relation to the equations.
A basic component in Internet applications is the electronic mail and its various implications. The paper proposes a mechanism for automatically classifying emails and create dynamic groups that belong to these messages. Proposed mechanisms will be based on natural language processing techniques and will be designed to facilitate human-machine interaction in this direction.
With the rapid growth of e-Commerce, online product search has emerged as a popular and effective paradigm for customers to find desired products and engage in online shopping. However, there is still a big gap between the products that customers really desire to purchase and relevance of products that are suggested in response to a query from the customer. In this paper, we propose a robust way of predicting relevance scores given a search query and a product, using techniques involving machine learning, natural language processing and information retrieval. We compare conventional information retrieval models such as BM25 and Indri with deep learning models such as word2vec, sentence2vec and paragraph2vec. We share some of our insights and findings from our experiments.
One of the ultimate goals of e-commerce platforms is to satisfy various shopping needs for their customers. Much efforts are devoted to creating taxonomies or ontologies in e-commerce towards this goal. However, user needs in e-commerce are still not well defined, and none of the existing ontologies has the enough depth and breadth for universal user needs understanding. The semantic gap in-between prevents shopping experience from being more intelligent. In this paper, we propose to construct a large-scale e-commerce cognitive concept net named AliCoCo, which is practiced in Alibaba, the largest Chinese e-commerce platform in the world. We formally define user needs in e-commerce, then conceptualize them as nodes in the net. We present details on how AliCoCo is constructed semi-automatically and its successful, ongoing and potential applications in e-commerce.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
