Social tags are known to be a valuable source of information for image retrieval and organization. However, contrary to the conventional document retrieval, rich tag frequency information in social sharing systems, such as Flickr, is not available, thus we cannot directly use the tag frequency (analogous to the term frequency in a document) to represent the relevance of tags. Many heuristic approaches have been proposed to address this problem, among which the well-known neighbor voting based approaches are the most effective methods. The basic assumption of these methods is that a tag is considered as relevant to the visual content of a target image if this tag is also used to annotate the visual neighbor images of the target image by lots of different users. The main limitation of these approaches is that they treat the voting power of each neighbor image either equally or simply based on its visual similarity. In this paper, we cast the social tag relevance learning problem as an adaptive teleportation random walk process on the voting graph.In particular, we model the relationships among images by constructing a voting graph, and then propose an adaptive teleportation random walk, in which a confidence factor is introduced to control the teleportation probability, on the voting graph. Through this process, direct and indirect relationships among images can be explored to cooperatively estimate the tag relevance. To quantify the performance of our approach, we compare it with state-of-the-art methods on two publicly available datasets (NUS-WIDE and MIR Flickr). The results indicate that our method achieves substantial performance gains on these datasets.

Wikipedia is widely considered the largest and most up-todate online encyclopedia, with its content being continuously maintained by a supporting community. In many cases, real-life events like new scientific findings, resignations, deaths, or catastrophes serve as triggers for collaborative editing of articles about affected entities such as persons or countries. In this paper, we conduct an in-depth analysis of event-related updates in Wikipedia by examining different indicators for events including language, meta annotations, and update bursts. We then study how these indicators can be employed for automatically detecting eventrelated updates. Our experiments on event extraction, clustering, and summarization show promising results towards generating entity-specific news tickers and timelines.

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The first AAAI Conference on Human Computation and Crowdsourcing (HCOMP-2013) was be held November 6-9, 2013 in Palm Springs, California. Three workshops took place on Saturday, November 9th: Crowdsourcing at Scale (full day), Human and Machine Learning in Games (full day) and Scaling Speech, Language Understanding and Dialogue through Crowdsourcing (half day). This report summarizes the activities of those three events.

Over the last years, repurposed agents have provided growing evidence of fast implementation in oncology treatment such as certain antimalarial, anthelmintic, antibiotics, anti-inflammatory, antihypertensive, antihyperlipidemic, antidiabetic agents. In this study, the four agents of choice were present in our patients’ daily treatment for nonmalignant-associated pathology and have known, light toxicity profiles. It is quite common for a given patient’s daily administration schedule to include two or three of these drugs for the duration of their treatment. We chose to review the latest literature concerning metformin, employed as a first-line treatment for type 2 diabetes; mebendazole, as an anthelmintic; atorvastatin, as a cholesterol-lowering drug; propranolol, used in cardiovascular diseases as a nonspecific inhibitor of beta-1 and beta-2 adrenergic receptors. At the same time, certain key action mechanisms make them feasible antitumor agents such as for mitochondrial ETC inhibition, activation of the enzyme adenosine monophosphate-activated protein kinase, amelioration of endogenous hyperinsulinemia, inhibition of selective tyrosine kinases (i.e., VEGFR2, TNIK, and BRAF), and mevalonate pathway inhibition. Despite the abundance of results from in vitro and in vivo studies, the only solid data from randomized clinical trials confirm metformin-related oncological benefits for only a small subset of nondiabetic patients with HER2-positive breast cancer and early-stage colorectal cancer. At the same time, clinical studies confirm metformin-related detrimental/lack of an effect for lung, breast, prostate cancer, and glioblastoma. For atorvastatin we see a clinical oncological benefit in patients and head and neck cancer, with a trend towards radioprotection of critical structures, thus supporting the role of atorvastatin as a promising agent for concomitant association with radiotherapy. Propranolol-related increased outcomes were seen in clinical studies in patients with melanoma, breast cancer, and sarcoma.

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Adenocarcinoma and adenosquamous carcinoma (AS) are 2 rare histological types of cervix uteri cancer constituting almost 20% of all cervix cancers, leading to a lack in patient management guidelines. We report the case of a 32-year-old woman with an oligometastatic cervix AS for which a multimodal treatment approach was used. Despite the patient’s bad prognosis, a complete response was achieved, which further resulted in excellent local control and prolonged survival. This case report serves the purpose of encouraging multidisciplinary team work and out-of-the-box thinking that should result in an individualized treatment for rare cancer subtypes.