By Dosam Hwang, Jason J. Jung, Ngoc Thanh Nguyen

This publication constitutes the refereed court cases of the sixth overseas convention on Collective Intelligence, ICCCI 2014, held in Seoul, Korea, in September 2014. The 70 complete papers awarded have been rigorously reviewed and chosen from 205 submissions. They handle issues akin to wisdom integration, information mining for collective processing, fuzzy, modal and collective structures, nature encouraged structures, language processing structures, social networks and semantic internet, agent and multi-agent structures, type and clustering tools, multi-dimensional info processing, internet platforms, clever determination making, equipment for scheduling, photo and video processing, collective intelligence in internet structures, computational swarm intelligence, cooperation and collective knowledge.

Show description

Read Online or Download Computational Collective Intelligence. Technologies and Applications: 6th International Conference, ICCCI 2014, Seoul, Korea, September 24-26, 2014. Proceedings PDF

Similar data mining books

Knowledge-Based Intelligent Information and Engineering Systems: 11th International Conference, KES 2007, Vietri sul Mare, Italy, September 12-14,

The 3 quantity set LNAI 4692, LNAI 4693, and LNAI 4694, represent the refereed complaints of the eleventh overseas convention on Knowledge-Based clever info and Engineering structures, KES 2007, held in Vietri sul Mare, Italy, September 12-14, 2007. The 409 revised papers provided have been conscientiously reviewed and chosen from approximately 1203 submissions.

Multimedia Data Mining and Analytics: Disruptive Innovation

This booklet offers clean insights into the innovative of multimedia facts mining, reflecting how the examine concentration has shifted in the direction of networked social groups, cellular units and sensors. The paintings describes how the historical past of multimedia facts processing should be seen as a series of disruptive ideas.

What stays in Vegas: the world of personal data—lifeblood of big business—and the end of privacy as we know it

The best danger to privateness this present day isn't the NSA, yet good-old American businesses. web giants, best outlets, and different companies are voraciously collecting information with little oversight from anyone.
In Las Vegas, no corporation is aware the price of information higher than Caesars leisure. Many millions of enthusiastic consumers pour during the ever-open doorways in their casinos. the key to the company’s luck lies of their one unequalled asset: they recognize their consumers in detail through monitoring the actions of the overpowering majority of gamblers. They comprehend precisely what video games they prefer to play, what meals they take pleasure in for breakfast, once they like to stopover at, who their favourite hostess can be, and precisely the way to continue them coming again for more.
Caesars’ dogged data-gathering equipment were such a success that they have got grown to develop into the world’s biggest on line casino operator, and feature encouraged businesses of all types to ramp up their very own information mining within the hopes of boosting their unique advertising and marketing efforts. a few do that themselves. a few depend on facts agents. Others truly input an ethical grey sector that are meant to make American shoppers deeply uncomfortable.
We stay in an age while our own details is harvested and aggregated even if we adore it or now not. And it's turning out to be ever tougher for these companies that decide upon to not interact in additional intrusive info amassing to compete with those who do. Tanner’s well timed caution resounds: certain, there are lots of merits to the loose stream of all this information, yet there's a darkish, unregulated, and harmful netherworld besides.

Machine Learning in Medical Imaging: 7th International Workshop, MLMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings

This ebook constitutes the refereed court cases of the seventh overseas Workshop on computer studying in clinical Imaging, MLMI 2016, held together with MICCAI 2016, in Athens, Greece, in October 2016. The 38 complete papers awarded during this quantity have been rigorously reviewed and chosen from 60 submissions.

Extra resources for Computational Collective Intelligence. Technologies and Applications: 6th International Conference, ICCCI 2014, Seoul, Korea, September 24-26, 2014. Proceedings

Example text

Fuzzification. Fuzzification is the process of deriving linguistic values for linguistic variables using crisp inputs by defining proper membership functions. The parameters that are considered by expert for FP reduction are size of initial lesion, lesion likelihood, intensity of individual voxel/pixel and its neighboring intensity. Based on mentioned parameters four linguistic variables that inferencing will be done based on them are defined namely MRI-Intensity, Neighboring-MRIIntensity, Segmentation-Result, and Lesion-Likelihood.

The main burden of reduction is carried out by FFPR component which is a complete fuzzy expert system with three processes namely Fuzzification, Inferencing using experts rule base, and Defuzzification. In the following sections the details of each component will be explained. Fig. 2. 1 H. Khastavaneh and H. Haron Model Inputs To eliminate the FP voxel/pixels, three inputs are considered in this model. These inputs are the intensity of original MRI, initial lesion mask of MRI, and atlas prior knowledge.

3. Lx (γ, ∈ I) is a regular language. Proof. Case 1. Let γ = (V, T, A, R, μ, ×) be a fuzzy splicing system where A = {(x1 , μ1 ), (x2 , μ2 ), . . , (xn , μn )} and 0 < μi < 1 for all 1 ≤ i ≤ n. Then, it is clear that k k+1 μij , μij ∈ {μ1 , . . , μn }, 1 ≤ j ≤ m. μij > j=1 j=1 26 F. Karimi et al. Hence, there exists m ∈ N such that m μij < α, μij ∈ {μ1 , . . , μn }, 1 ≤ j ≤ m. j=1 Thus, a finite number of μ(x)s, x ∈ Lf (γ), can satisfy the inequality μ(x) > α. Case 2. It is clear that for x ∈ {s, w}, Lc (γ) = Lx (γ, > α) ∪ Lx (γ, ≤ α).

Download PDF sample

Rated 4.18 of 5 – based on 17 votes