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<rdf:RDF xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><channel rdf:about="https://www.bibsonomy.org/tag/prediction"><title>BibSonomy bookmarks for /tag/prediction</title><link>https://www.bibsonomy.org/tag/prediction</link><description>BibSonomy RSS Feed for /tag/prediction</description><items><rdf:Seq><rdf:li rdf:resource="https://towardsdatascience.com/lstm-time-series-forecasting-predicting-stock-prices-using-an-lstm-model-6223e9644a2f"/><rdf:li rdf:resource="https://forum.pyro.ai/t/bayesian-regression-predictions/1115/8"/><rdf:li rdf:resource="https://github.com/pyro-ppl/pyro/issues/1930"/><rdf:li rdf:resource="https://medium.com/@alexrachnog/financial-forecasting-with-probabilistic-programming-and-pyro-db68ab1a1dba"/><rdf:li rdf:resource="https://stats.stackexchange.com/questions/61783/bias-and-variance-in-leave-one-out-vs-k-fold-cross-validation"/><rdf:li rdf:resource="https://stats.stackexchange.com/questions/18348/differences-between-cross-validation-and-bootstrapping-to-estimate-the-predictio"/><rdf:li rdf:resource="https://github.com/marcotcr/lime"/><rdf:li rdf:resource="https://www.technologyreview.com/s/609048/the-seven-deadly-sins-of-ai-predictions/"/><rdf:li rdf:resource="https://www.gjopen.com/"/><rdf:li rdf:resource="https://www.metaculus.com/questions/"/><rdf:li rdf:resource="https://predictionbook.com/"/><rdf:li rdf:resource="https://github.com/ritchieng/NumNum"/><rdf:li rdf:resource="https://stats.stackexchange.com/questions/1194/practical-thoughts-on-explanatory-vs-predictive-modeling"/><rdf:li rdf:resource="https://de.slideshare.net/gshmueli/to-explain-or-to-predict-13587471"/><rdf:li rdf:resource="https://blog.openai.com/unsupervised-sentiment-neuron/"/><rdf:li rdf:resource="http://www.intrade.com/"/><rdf:li rdf:resource="http://www.predictionmarketjournal.com/"/><rdf:li rdf:resource="http://inklingmarkets.blogspot.com/"/><rdf:li rdf:resource="http://www.consensuspoint.com/blog/"/><rdf:li rdf:resource="http://newsfutures.wordpress.com/"/></rdf:Seq></items></channel><item rdf:about="https://towardsdatascience.com/lstm-time-series-forecasting-predicting-stock-prices-using-an-lstm-model-6223e9644a2f"><title>Time-Series Forecasting: Predicting Stock Prices Using An LSTM Model | by Serafeim Loukas | Towards Data Science</title><description>I thought this was Renee&#039;s website! (Maybe hers is becomingdatascience.com?) Most machine learning (ML) models use samples / examples observations as input. This data lacks any time dimension. Time-series forecasting models are...</description><link>https://towardsdatascience.com/lstm-time-series-forecasting-predicting-stock-prices-using-an-lstm-model-6223e9644a2f</link><dc:creator>3lli3</dc:creator><dc:date>2021-06-29T05:31:55+02:00</dc:date><dc:subject>lstm ml prediction price stock time-series </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;I thought this was Renee&amp;#039;s website! (Maybe hers is becomingdatascience.com?) Most machine learning (ML) models use samples / examples observations as input. This data lacks any time dimension. Time-series forecasting models are...&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/lstm"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/ml"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/price"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/stock"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/time-series"/></rdf:Bag></taxo:topics></item><item rdf:about="https://forum.pyro.ai/t/bayesian-regression-predictions/1115/8"><title>Bayesian regression predictions - Tutorials - Pyro Discussion Forum</title><description></description><link>https://forum.pyro.ai/t/bayesian-regression-predictions/1115/8</link><dc:creator>becker</dc:creator><dc:date>2020-05-28T00:44:17+02:00</dc:date><dc:subject>bayes pyro bayesian regression sample prediction </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2020-05-28T00:44:17+02:00&#034; 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data-versiondate=&#034;2020-05-28T00:44:05+02:00&#034; href=&#034;https://github.com/pyro-ppl/pyro/issues/1930&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://github.com/pyro-ppl/pyro/issues/1930&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/pyro"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayesian"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/regression"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/sample"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/></rdf:Bag></taxo:topics></item><item rdf:about="https://medium.com/@alexrachnog/financial-forecasting-with-probabilistic-programming-and-pyro-db68ab1a1dba"><title>Financial forecasting with probabilistic programming and Pyro</title><description></description><link>https://medium.com/@alexrachnog/financial-forecasting-with-probabilistic-programming-and-pyro-db68ab1a1dba</link><dc:creator>becker</dc:creator><dc:date>2020-05-28T00:43:54+02:00</dc:date><dc:subject>bayes pyro bayesian regression sample prediction </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2020-05-28T00:43:54+02:00&#034; href=&#034;https://medium.com/@alexrachnog/financial-forecasting-with-probabilistic-programming-and-pyro-db68ab1a1dba&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://medium.com/@alexrachnog/financial-forecasting-with-probabilistic-programming-and-pyro-db68ab1a1dba&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayes"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/pyro"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayesian"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/regression"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/sample"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/></rdf:Bag></taxo:topics></item><item rdf:about="https://stats.stackexchange.com/questions/61783/bias-and-variance-in-leave-one-out-vs-k-fold-cross-validation"><title>machine learning - Bias and variance in leave-one-out vs K-fold cross validation - Cross Validated</title><description></description><link>https://stats.stackexchange.com/questions/61783/bias-and-variance-in-leave-one-out-vs-k-fold-cross-validation</link><dc:creator>becker</dc:creator><dc:date>2018-12-12T23:20:46+01:00</dc:date><dc:subject>bias variance kfold fold leave one out leaveoneout evaluation prediction classfier classification </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2018-12-12T23:20:46+01:00&#034; href=&#034;https://stats.stackexchange.com/questions/61783/bias-and-variance-in-leave-one-out-vs-k-fold-cross-validation&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://stats.stackexchange.com/questions/61783/bias-and-variance-in-leave-one-out-vs-k-fold-cross-validation&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bias"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/variance"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/kfold"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/fold"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/leave"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/one"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/out"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/leaveoneout"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/evaluation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/classfier"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/classification"/></rdf:Bag></taxo:topics></item><item rdf:about="https://stats.stackexchange.com/questions/18348/differences-between-cross-validation-and-bootstrapping-to-estimate-the-predictio"><title>predictive models - Differences between cross validation and bootstrapping to estimate the prediction error - Cross Validated</title><description></description><link>https://stats.stackexchange.com/questions/18348/differences-between-cross-validation-and-bootstrapping-to-estimate-the-predictio</link><dc:creator>becker</dc:creator><dc:date>2018-12-12T23:14:09+01:00</dc:date><dc:subject>bootstrapping evaluation kfold cross validation boot strapping classification prediction </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2018-12-12T23:14:09+01:00&#034; href=&#034;https://stats.stackexchange.com/questions/18348/differences-between-cross-validation-and-bootstrapping-to-estimate-the-predictio&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://stats.stackexchange.com/questions/18348/differences-between-cross-validation-and-bootstrapping-to-estimate-the-predictio&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bootstrapping"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/evaluation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/kfold"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/cross"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/validation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/boot"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/strapping"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/classification"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/></rdf:Bag></taxo:topics></item><item rdf:about="https://github.com/marcotcr/lime"><title>GitHub - marcotcr/lime: Lime: Explaining the predictions of any machine learning classifier</title><description>lime - Lime: Explaining the predictions of any machine learning classifier</description><link>https://github.com/marcotcr/lime</link><dc:creator>michelc</dc:creator><dc:date>2018-02-06T13:23:12+01:00</dc:date><dc:subject>explanation intuition learning machine openSource prediction </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;lime - Lime: Explaining the predictions of any machine learning classifier&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/explanation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/intuition"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/learning"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/machine"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/openSource"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/></rdf:Bag></taxo:topics></item><item rdf:about="https://www.technologyreview.com/s/609048/the-seven-deadly-sins-of-ai-predictions/"><title>The Seven Deadly Sins of AI Predictions – MIT Technology Review 06.10.2017</title><description>Mistaken extrapolations, limited imagination, and other common mistakes that distract us from thinking more productively about the future.</description><link>https://www.technologyreview.com/s/609048/the-seven-deadly-sins-of-ai-predictions/</link><dc:creator>meneteqel</dc:creator><dc:date>2017-10-15T22:50:27+02:00</dc:date><dc:subject>artificial_intelligence exponentials future_of_work magic metaphor prediction digitisation </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Mistaken extrapolations, limited imagination, and other common mistakes that distract us from thinking more productively about the future.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/artificial_intelligence"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/exponentials"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/future_of_work"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/magic"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/metaphor"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/digitisation"/></rdf:Bag></taxo:topics></item><item rdf:about="https://www.gjopen.com/"><title>Good Judgment® Open</title><description></description><link>https://www.gjopen.com/</link><dc:creator>bshanks</dc:creator><dc:date>2017-09-18T21:52:33+02:00</dc:date><dc:subject>brier forecast predict prediction </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; 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data-versiondate=&#034;2017-09-18T21:38:46+02:00&#034; href=&#034;https://predictionbook.com/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://predictionbook.com/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/brier"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/forecast"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/predict"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/></rdf:Bag></taxo:topics></item><item rdf:about="https://github.com/ritchieng/NumNum"><title>ritchieng/NumNum: Multi-digit prediction from Google Street&#039;s images using deep CNN with TensorFlow, OpenCV and Python.</title><description>NumNum - Multi-digit prediction from Google Street&#039;s images using deep CNN with TensorFlow, OpenCV and Python.</description><link>https://github.com/ritchieng/NumNum</link><dc:creator>nosebrain</dc:creator><dc:date>2017-08-07T15:22:24+02:00</dc:date><dc:subject>cnn digit multi numnum prediction tensorflow </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;NumNum - Multi-digit prediction from Google Street&amp;#039;s images using deep CNN with TensorFlow, OpenCV and Python.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/cnn"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/digit"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/multi"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/numnum"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tensorflow"/></rdf:Bag></taxo:topics></item><item rdf:about="https://stats.stackexchange.com/questions/1194/practical-thoughts-on-explanatory-vs-predictive-modeling"><title>Practical thoughts on explanatory vs. predictive modeling - Cross Validated</title><description></description><link>https://stats.stackexchange.com/questions/1194/practical-thoughts-on-explanatory-vs-predictive-modeling</link><dc:creator>becker</dc:creator><dc:date>2017-07-10T10:43:05+02:00</dc:date><dc:subject>predictive predict prediction explain explainatory explanation vs model modeling </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; 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data-versiondate=&#034;2017-07-10T10:34:24+02:00&#034; href=&#034;https://de.slideshare.net/gshmueli/to-explain-or-to-predict-13587471&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://de.slideshare.net/gshmueli/to-explain-or-to-predict-13587471&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/predict"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/explain"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/vs"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/explanation"/></rdf:Bag></taxo:topics></item><item rdf:about="https://blog.openai.com/unsupervised-sentiment-neuron/"><title>Unsupervised sentiment neuron</title><description>We’ve developed an unsupervised system which learns an excellent representation of sentiment.</description><link>https://blog.openai.com/unsupervised-sentiment-neuron/</link><dc:creator>hotho</dc:creator><dc:date>2017-04-25T08:23:51+02:00</dc:date><dc:subject>character classification prediction sentiment vector </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;We’ve developed an unsupervised system which learns an excellent representation of sentiment.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/character"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/classification"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/sentiment"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/vector"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.intrade.com/"><title>Intrade Prediction Markets</title><description></description><link>http://www.intrade.com/</link><dc:creator>bshanks</dc:creator><dc:date>2016-12-12T10:02:24+01:00</dc:date><dc:subject>Bookmarks trading prediction market eventFutures futures predictionmarket predictionmarkets </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-12-12T10:02:24+01:00&#034; href=&#034;http://www.intrade.com/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.intrade.com/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Bookmarks"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/trading"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/market"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/eventFutures"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/futures"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/predictionmarket"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/predictionmarkets"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.predictionmarketjournal.com/"><title>Home</title><description></description><link>http://www.predictionmarketjournal.com/</link><dc:creator>bshanks</dc:creator><dc:date>2016-12-12T10:02:21+01:00</dc:date><dc:subject>Bookmarks predictionmarkets prediction journal markets academic </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-12-12T10:02:21+01:00&#034; href=&#034;http://www.predictionmarketjournal.com/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.predictionmarketjournal.com/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Bookmarks"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/predictionmarkets"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/journal"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/markets"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/academic"/></rdf:Bag></taxo:topics></item><item rdf:about="http://inklingmarkets.blogspot.com/"><title>Inkling Markets</title><description></description><link>http://inklingmarkets.blogspot.com/</link><dc:creator>bshanks</dc:creator><dc:date>2016-12-12T10:02:20+01:00</dc:date><dc:subject>Bookmarks prediction markets predictionmarkets </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-12-12T10:02:20+01:00&#034; href=&#034;http://inklingmarkets.blogspot.com/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://inklingmarkets.blogspot.com/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Bookmarks"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/markets"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/predictionmarkets"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.consensuspoint.com/blog/"><title>Prediction Markets Blog by Consensus Point</title><description></description><link>http://www.consensuspoint.com/blog/</link><dc:creator>bshanks</dc:creator><dc:date>2016-12-12T10:02:20+01:00</dc:date><dc:subject>Bookmarks predictionmarkets prediction market </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-12-12T10:02:20+01:00&#034; href=&#034;http://www.consensuspoint.com/blog/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.consensuspoint.com/blog/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Bookmarks"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/predictionmarkets"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/market"/></rdf:Bag></taxo:topics></item><item rdf:about="http://newsfutures.wordpress.com/"><title>Newsfutures’ Blog</title><description></description><link>http://newsfutures.wordpress.com/</link><dc:creator>bshanks</dc:creator><dc:date>2016-12-12T10:02:20+01:00</dc:date><dc:subject>Bookmarks markets predictionmarkets prediction </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-12-12T10:02:20+01:00&#034; href=&#034;http://newsfutures.wordpress.com/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://newsfutures.wordpress.com/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Bookmarks"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/markets"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/predictionmarkets"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/prediction"/></rdf:Bag></taxo:topics></item></rdf:RDF>