Research on similarity algorithm of normal cloud based on double envelope curves

Author(s):  
Huabin Cheng ◽  
Yonghong Chen
2021 ◽  
Vol 1166 (1) ◽  
pp. 012016
Author(s):  
Swati Jain ◽  
Suraj Prakash Narayan ◽  
Nalini Meena ◽  
Rupesh Kumar Dewang ◽  
Utkarsh Bhartiya ◽  
...  

2021 ◽  
pp. 135918352110288
Author(s):  
Eva Hemmungs Wirtén

This article is about an everyday paper object: an envelope. However, as opposed to most other flat paper containers, the enveloppe Soleau can only be bought from L’Institut national de la propriété industrielle (INPI) in Paris. At the cost of €15 you get a perforated, double-compartment envelope allowing you to constitute proof of creation and assign a precise date to your idea or project. But the enveloppe Soleau is something much more than just a simple and cheap way by which you can prove priority in any creative domain. It is a material footprint anchored to centuries of practices associated with disclosure and secrecy, a gateway into the infrastructure of the intellectual property system and its complicated relationship to the forms of knowledge it purports to hold. The purpose of this article is to consider the making of the enveloppe Soleau as a bureaucratic document, a material device performing a particular kind of legal paperwork. In four different vignettes, the article tracks the material becoming of the enveloppe Soleau as an evidentiary receptacle, beginning by going back to early modern practices of secrecy and priority, continuing with its consolidation in two patents (from 1910 and 1911) to the inventor Eugène Soleau (1852–1929), and ending up, in 2016, dematerialized in the e-Soleau. As a bureaucratic document, the enveloppe Soleau shows just how much work a mundane paper object can perform, navigating a particular materiality (a patented double envelope); formalized processes of proof (where perforations have legal significance); the practices of double archiving (in an institution and with the individual) and strict temporal limitations (a decade). Ultimately, the enveloppe Soleau travels between the material and immaterial, between private and public, between secrecy and disclosure, but also between what we perceive of as the outside and inside of the intellectual property system.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Triyanna Widiyaningtyas ◽  
Indriana Hidayah ◽  
Teguh B. Adji

AbstractCollaborative filtering is one of the most widely used recommendation system approaches. One issue in collaborative filtering is how to use a similarity algorithm to increase the accuracy of the recommendation system. Most recently, a similarity algorithm that combines the user rating value and the user behavior value has been proposed. The user behavior value is obtained from the user score probability in assessing the genre data. The problem with the algorithm is it only considers genre data for capturing user behavior value. Therefore, this study proposes a new similarity algorithm – so-called User Profile Correlation-based Similarity (UPCSim) – that examines the genre data and the user profile data, namely age, gender, occupation, and location. All the user profile data are used to find the weights of the similarities of user rating value and user behavior value. The weights of both similarities are obtained by calculating the correlation coefficients between the user profile data and the user rating or behavior values. An experiment shows that the UPCSim algorithm outperforms the previous algorithm on recommendation accuracy, reducing MAE by 1.64% and RMSE by 1.4%.


2009 ◽  
Vol 36 (10) ◽  
pp. 12480-12490 ◽  
Author(s):  
Min Liu ◽  
Weiming Shen ◽  
Qi Hao ◽  
Junwei Yan

Author(s):  
Kithsiri Jayakodi ◽  
Madhushi Bandara ◽  
Indika Perera ◽  
Dulani Meedeniya

Assessment usually plays an indispensable role in the education and it is the prime indicator of student learning achievement. Exam questions are the main form of assessment used in learning. Setting appropriate exam questions to achieve the desired outcome of the course is a challenging work for the examiner. Therefore this research is mainly focused to categorize the exam questions automatically into its learning levels using Bloom’s taxonomy. Natural Language Processing (NLP) techniques such as tokenization, stop word removal, lemmatization and tagging were used before generating the rule set to be used for this classification. WordNet similarity algorithms with NLTK and cosine similarity algorithm were developed to generate a unique set of rules to identify the question category and the weight for each exam question according to Bloom’s taxonomy. These derived rules make it easy to analyze the exam questions. Evaluators can redesign their exam papers based on the outcome of the evaluation process. A sample of examination questions of the Department of Computing and Information Systems, Wayamba University, Sri Lanka was used for the evaluation; weight assignment was done based on the total value generated from both WordNet algorithm and the cosine algorithm. Identified question categories were confirmed by a domain expert. The generated rule set indicated over 70% accuracy.


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