Multi-label classification has many applications in the text categorization, biology and medical diagnosis, in which multiple class labels can be assigned to each training instance simultaneously. As it is often the case that there are relationships between the labels, extracting the existing relationships between the labels and taking advantage of them during the training or prediction phases ...

‎let $g$ be a graph with vertex set $v(g)$ and edge set $x(g)$ and consider the set $a={0,1}$‎. ‎a mapping $l:v(g)longrightarrow a$ is called binary vertex labeling of $g$ and $l(v)$ is called the label of the vertex $v$ under $l$‎. ‎in this paper we introduce a new kind of graph energy for the binary labeled graph‎, ‎the labeled graph energy $e_{l}(g)$‎. ‎it depends on the underlying graph $g$...

let $g=(v‎, ‎e)$ be a graph with $p$ vertices and $q$ edges‎. ‎an emph{acyclic‎ ‎graphoidal cover} of $g$ is a collection $psi$ of paths in $g$‎ ‎which are internally-disjoint and cover each edge of the graph‎ ‎exactly once‎. ‎let $f‎: ‎vrightarrow {1‎, ‎2‎, ‎ldots‎, ‎p}$ be a bijective‎ ‎labeling of the vertices of $g$‎. ‎let $uparrow!g_f$ be the‎ ‎directed graph obtained by orienting the...

Social media have enjoyed a rapidly increasing adoption among users in recent years. Millions of users execute billions of actions (in form of tweets, messages, replies, likes, etc.) every day. The massive amount of social interactions online has contributed to the proliferation of social advertising. Alongside the interest in online and social advertising, Twitter has introduced several advert...

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We investigate paid endorsement as a crowd-sourcing social advertising mechanism that allows advertisers to bypass publishers (e.g., Facebook) and recruit individual endorsers of their own choice at affordable prices. Specifically, we investigate (i) how incentives affect endorsers’ participation and effectiveness, (ii) what types of endorsers are most effective in generating online engagement ...

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the efficient detection of charged biomolecules by biosensor with appropriate semiconducting nanomaterials and with optimum device geometry has caught tremendous research interest in the present decade. here, the performance of various label-free electronic biosensors to detect bio-molecules is investigated by simulation technique. silicon nanowire sensor, nanosphere sensor and double gate fiel...

Artificial intelligence techniques aimed at more naturally simulating human comprehension fit the paradigm of multi-label classification. Generally, an enormous amount of high-quality multi-label data is needed to form a multi-label classifier. The creation of such datasets is usually expensive and timeconsuming. A lower cost way to obtain multi-label datasets for use with such comprehension–si...