Also, please include an introduction to yourself (University, department), past experience in machine learning, language proficiency, etc at the beginning of the proposal.
Best regards. On Fri, Mar 25, 2016 at 5:47 PM, Maheshakya Wijewardena <mahesha...@wso2.com > wrote: > Hi Mahesh, > > Thank you for sending the draft. Please submit it as soon as possible. > > Few high level comments: > > In the proposal, you must specifically mention that this will be > implemented as a Siddhi extension that can operate directly on incoming > streams. > > Also, you need to have a time line for the project, A sample looks like: > > May 1- May 20 - Community bonding period - Getting familiar with the > platform and discussing implementation methods. > May 20 - May 30 - Implementing streaming k-means, > ----- > ----- > July 20-24 - Writing examples > July 24-18 - Documentation > > This should end before pencils down date. Refer to the correct time line > given in GSoC site. > > The implementation details of the the streaming algorithms looks fine. > > Best regards. > > > On Fri, Mar 25, 2016 at 5:23 PM, Mahesh Dananjaya < > dananjayamah...@gmail.com> wrote: > >> Hi Maheshakya, >> this is my draft proposal. >> >> https://docs.google.com/document/d/1apZfEXZXEH5GwSwS7hARINbGw5_zinxWdZjEmyqfKu4/edit?usp=sha >> <https://docs.google.com/document/d/1apZfEXZXEH5GwSwS7hARINbGw5_zinxWdZjEmyqfKu4/edit?usp=sharing> >> ring >> can you ple check this and see whether it is correct.thank you. >> BR, >> Mahesh >> >> >> On Mon, Mar 21, 2016 at 1:15 PM, Maheshakya Wijewardena < >> mahesha...@wso2.com> wrote: >> >>> Hi Mahesh, >>> >>> The deadline for submitting your proposals is on March 25th, 2016, >>> therefore please start writing the proposal and get feedback. >>> >>> Best regards. >>> >>> On Tue, Mar 15, 2016 at 4:14 PM, Mahesh Dananjaya < >>> dananjayamah...@gmail.com> wrote: >>> >>>> Hi Maheshakaya, >>>> Ok.I have been trying some examples and try to split them and train >>>> incrementally. Still doing that. i have been adding them to my github repo >>>> too. https://github.com/dananjayamahesh/GSOC2016 . i saw that there is >>>> only scala API support for those streaming algorithms in Spark. so my task >>>> is to develop Java API. will let you nkow my progress.thank you very much. >>>> BR, >>>> Mahesh >>>> >>>> On Tue, Mar 15, 2016 at 3:21 PM, Maheshakya Wijewardena < >>>> mahesha...@wso2.com> wrote: >>>> >>>>> Hi Mahesh, >>>>> >>>>> No you don't need to use Hadoop at any stage in this project. >>>>> Everything you need is in Spark (regarding ML algorithms). >>>>> You can also use Spark MLLibs methods to randomly split datasets. >>>>> >>>>> Best regards. >>>>> >>>>> On Mon, Mar 14, 2016 at 1:28 PM, Mahesh Dananjaya < >>>>> dananjayamah...@gmail.com> wrote: >>>>> >>>>>> Hi Maheshakya, >>>>>> I am writing some java programs and try to break the dataset into >>>>>> several pieces and train a model repeatedly with those data sets using >>>>>> Spark MLLib. Do i have to do anything with Hadoop at this stage, because >>>>>> i >>>>>> am working with a standalone mode.thank you. >>>>>> BR, >>>>>> Mahesh. >>>>>> >>>>>> On Sun, Mar 13, 2016 at 6:30 PM, Maheshakya Wijewardena < >>>>>> mahesha...@wso2.com> wrote: >>>>>> >>>>>>> Hi Mahesh, >>>>>>> >>>>>>> You don't have to look into carbon-ml. >>>>>>> >>>>>>> Best regards. >>>>>>> >>>>>>> On Sun, Mar 13, 2016 at 5:49 PM, Mahesh Dananjaya < >>>>>>> dananjayamah...@gmail.com> wrote: >>>>>>> >>>>>>>> Hi maheshakya, >>>>>>>> i am working on some examples related to Spark and ML.is there >>>>>>>> anything to do with carbon-ml. I think i dont need to look into that >>>>>>>> one.do >>>>>>>> i? >>>>>>>> BR, >>>>>>>> Mahesh >>>>>>>> >>>>>>>> On Tue, Mar 8, 2016 at 11:55 AM, Maheshakya Wijewardena < >>>>>>>> mahesha...@wso2.com> wrote: >>>>>>>> >>>>>>>>> Hi Mahesh, >>>>>>>>> >>>>>>>>> does that Scala API is with your current product or repo? >>>>>>>>> >>>>>>>>> >>>>>>>>> No, we don't have the Scala API included. What we want is to >>>>>>>>> design the Java implementations of those algorithms to train with >>>>>>>>> mini-batches of streaming data with the help of the aforementioned >>>>>>>>> methods >>>>>>>>> so that we can include in as a CEP extension. >>>>>>>>> >>>>>>>>> As to clarify, please try to write a simple Java program using >>>>>>>>> Spark MLLib linear regression and k-means clustering with a sample >>>>>>>>> data set >>>>>>>>> (You can find alot of data sets from UCI repo[1]). You need to break >>>>>>>>> the >>>>>>>>> dataset into several pieces and train a model repeatedly with those. >>>>>>>>> After each training run, save the model information (such as >>>>>>>>> weights, intercepts for regression and cluster centers for clustering >>>>>>>>> - >>>>>>>>> please check the arguments of those methods I have mentioned and save >>>>>>>>> the >>>>>>>>> required information of the model) >>>>>>>>> When training a model we a new piece of data, use those methods to >>>>>>>>> initialize and put the save values for the arguments. This way you can >>>>>>>>> start from where you stopped in the previous run. >>>>>>>>> >>>>>>>>> Let us know your observations and feel free to ask if you need to >>>>>>>>> know anything more on this. >>>>>>>>> >>>>>>>>> We'll let you know what needs to be done to include this in CEP. >>>>>>>>> >>>>>>>>> Best regards. >>>>>>>>> >>>>>>>>> On Tue, Mar 8, 2016 at 10:59 AM, Mahesh Dananjaya < >>>>>>>>> dananjayamah...@gmail.com> wrote: >>>>>>>>> >>>>>>>>>> Hi Maheshakya, >>>>>>>>>> great.thank you.i already have ML and CEP and working more >>>>>>>>>> towards it. does that Scala API is with your current product or >>>>>>>>>> repo?. >>>>>>>>>> thank you. >>>>>>>>>> BR, >>>>>>>>>> Mahesh. >>>>>>>>>> >>>>>>>>>> On Sun, Mar 6, 2016 at 5:49 PM, Maheshakya Wijewardena < >>>>>>>>>> mahesha...@wso2.com> wrote: >>>>>>>>>> >>>>>>>>>>> Hi Mahesh, >>>>>>>>>>> >>>>>>>>>>> Please find the comments inline. >>>>>>>>>>> >>>>>>>>>>> does data stream is taken to ML as the event publisher's format >>>>>>>>>>>> through event publisher. Or we can use direct traffic that comes >>>>>>>>>>>> to event >>>>>>>>>>>> receiver, or else as streams >>>>>>>>>>>> >>>>>>>>>>> We intend to use the direct data as even streams. >>>>>>>>>>> >>>>>>>>>>> 1.) Those data coming from wso2 DAS to ML are coming as streams? >>>>>>>>>>>> >>>>>>>>>>> No, WSO2 ML doesn't use any even stream. The data stored in >>>>>>>>>>> tables in DAS is loaded into ML. >>>>>>>>>>> >>>>>>>>>>> 2.) Are there any incremental learning algorithms currently >>>>>>>>>>>> active in ML?you mentioned that there are and they are with scala >>>>>>>>>>>> API. So >>>>>>>>>>>> there is a streaming support with that Scala API. In that API >>>>>>>>>>>> which format >>>>>>>>>>>> the data is aquired to ML? >>>>>>>>>>>> >>>>>>>>>>> No, there are no incremental learning algorithms in ML. The >>>>>>>>>>> scala API is about Spark MLLib. MLLib supports streaming k-means >>>>>>>>>>> and other >>>>>>>>>>> generalized linear models (linear regression variants and logistic >>>>>>>>>>> regression) with Scala API. What they basically do in those >>>>>>>>>>> implementations >>>>>>>>>>> is retraining the trained models with mini batches when data >>>>>>>>>>> sequentially >>>>>>>>>>> arrives. There, the breaking of streaming data into mini batches is >>>>>>>>>>> done >>>>>>>>>>> with the help of Spark Streaming. But we do not intend to use Spark >>>>>>>>>>> streaming in our implementation. What we need to do is implement a >>>>>>>>>>> similar >>>>>>>>>>> behavior for event streams using the Java API. The Java API has the >>>>>>>>>>> following methods: >>>>>>>>>>> >>>>>>>>>>> - *createModel >>>>>>>>>>> >>>>>>>>>>> <http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/regression/LinearRegressionWithSGD.html#createModel%28org.apache.spark.mllib.linalg.Vector,%20double%29>* >>>>>>>>>>> (Vector >>>>>>>>>>> >>>>>>>>>>> <http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/linalg/Vector.html> >>>>>>>>>>> weights, >>>>>>>>>>> double intercept) - for GLMs >>>>>>>>>>> - *setInitialModel >>>>>>>>>>> >>>>>>>>>>> <http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/clustering/KMeans.html#setInitialModel%28org.apache.spark.mllib.clustering.KMeansModel%29>* >>>>>>>>>>> (KMeansModel >>>>>>>>>>> >>>>>>>>>>> <http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/clustering/KMeansModel.html> >>>>>>>>>>> model) >>>>>>>>>>> - for K means >>>>>>>>>>> >>>>>>>>>>> With the help of these methods, we can train models again with >>>>>>>>>>> newly arriving data, keeping the characteristics learned with the >>>>>>>>>>> previous >>>>>>>>>>> data. When implementing this, we need to pay attention to other >>>>>>>>>>> parameters >>>>>>>>>>> of incremental learning such as data horizon and data obsolescence >>>>>>>>>>> (indicated in the project ideas page). >>>>>>>>>>> We need to discuss on how to add these with CEP event streams. I >>>>>>>>>>> have added Suho into the thread for more clarification. >>>>>>>>>>> >>>>>>>>>>> Best regards. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On Sat, Mar 5, 2016 at 5:15 PM, Mahesh Dananjaya < >>>>>>>>>>> dananjayamah...@gmail.com> wrote: >>>>>>>>>>> >>>>>>>>>>>> Hi maheshakya, >>>>>>>>>>>> as we concerned to use WSO2 CEP to handle streaming data and >>>>>>>>>>>> implement the machine learning algorithms with Spark MLLib, does >>>>>>>>>>>> data >>>>>>>>>>>> stream is taken to ML as the event publisher's format through event >>>>>>>>>>>> publisher. Or we can use direct traffic that comes to event >>>>>>>>>>>> receiver, or >>>>>>>>>>>> else as streams. referring to >>>>>>>>>>>> https://docs.wso2.com/display/CEP410/User+Guide >>>>>>>>>>>> 1.) Those data coming from wso2 DAS to ML are coming as >>>>>>>>>>>> streams? >>>>>>>>>>>> 2.) Are there any incremental learning algorithms currently >>>>>>>>>>>> active in ML?you mentioned that there are and they are with scala >>>>>>>>>>>> API. So >>>>>>>>>>>> there is a streaming support with that Scala API. In that API >>>>>>>>>>>> which format >>>>>>>>>>>> the data is aquired to ML? >>>>>>>>>>>> >>>>>>>>>>>> thank you. >>>>>>>>>>>> BR, >>>>>>>>>>>> Mahesh. >>>>>>>>>>>> >>>>>>>>>>>> On Fri, Mar 4, 2016 at 2:03 PM, Maheshakya Wijewardena < >>>>>>>>>>>> mahesha...@wso2.com> wrote: >>>>>>>>>>>> >>>>>>>>>>>>> Hi Mahesh, >>>>>>>>>>>>> >>>>>>>>>>>>> We had to modify a the project scope a little to suit best for >>>>>>>>>>>>> the requirements. We will update the project idea with those >>>>>>>>>>>>> concerns soon >>>>>>>>>>>>> and let you know. >>>>>>>>>>>>> >>>>>>>>>>>>> We do not support streaming data in WSO2 Machine learner at >>>>>>>>>>>>> the moment. The new concern is to use WSO2 CEP to handle >>>>>>>>>>>>> streaming data and >>>>>>>>>>>>> implement the machine learning algorithms with Spark MLLib. You >>>>>>>>>>>>> can look at >>>>>>>>>>>>> the streaming k-means and streaming linear regression >>>>>>>>>>>>> implementations in >>>>>>>>>>>>> MLLib. Currently, the API is only for scala. Our need is to get >>>>>>>>>>>>> the Java >>>>>>>>>>>>> APIs of k-means and generalized linear models to support >>>>>>>>>>>>> incremental >>>>>>>>>>>>> learning with streaming data. This has to be done as mini-batch >>>>>>>>>>>>> learning >>>>>>>>>>>>> since these algorithms operates as stochastic gradient descents >>>>>>>>>>>>> so that any >>>>>>>>>>>>> learning with new data can be done on top of the previously >>>>>>>>>>>>> learned models. >>>>>>>>>>>>> So please go through the those APIs[1][2][3] and try to get an >>>>>>>>>>>>> idea. >>>>>>>>>>>>> Also please try to understand how event streams work in WSO2 >>>>>>>>>>>>> CEP [4][5]. >>>>>>>>>>>>> >>>>>>>>>>>>> Best regards. >>>>>>>>>>>>> >>>>>>>>>>>>> [1] >>>>>>>>>>>>> http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/regression/LinearRegressionWithSGD.html >>>>>>>>>>>>> [2] >>>>>>>>>>>>> http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/clustering/KMeans.html >>>>>>>>>>>>> [3] >>>>>>>>>>>>> http://spark.apache.org/docs/latest/api/java/org/apache/spark/mllib/classification/LogisticRegressionWithSGD.html >>>>>>>>>>>>> [4] >>>>>>>>>>>>> https://docs.wso2.com/display/CEP310/Working+with+Event+Streams >>>>>>>>>>>>> [5] >>>>>>>>>>>>> https://docs.wso2.com/display/CEP310/Working+with+Execution+Plans >>>>>>>>>>>>> >>>>>>>>>>>>> On Fri, Mar 4, 2016 at 11:26 AM, Mahesh Dananjaya < >>>>>>>>>>>>> dananjayamah...@gmail.com> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>>> Hi maheshakya, >>>>>>>>>>>>>> give me sometime to go through your ML package. Do current >>>>>>>>>>>>>> product have any stream data support?. i did some university >>>>>>>>>>>>>> projects >>>>>>>>>>>>>> related to machine learning with regressions,modelling, factor >>>>>>>>>>>>>> analysis, >>>>>>>>>>>>>> cluster analysis and classification problems (Discriminant >>>>>>>>>>>>>> Analysis) with >>>>>>>>>>>>>> SVM (Support Vector machines), Neural networks, LS >>>>>>>>>>>>>> classification and >>>>>>>>>>>>>> ML(Maximum likelihood). give me sometime to see how wso2 >>>>>>>>>>>>>> architecture >>>>>>>>>>>>>> works.then i can come up with good architecture.thank you. >>>>>>>>>>>>>> BR, >>>>>>>>>>>>>> Mahesh. >>>>>>>>>>>>>> >>>>>>>>>>>>>> On Wed, Mar 2, 2016 at 2:41 PM, Mahesh Dananjaya < >>>>>>>>>>>>>> dananjayamah...@gmail.com> wrote: >>>>>>>>>>>>>> >>>>>>>>>>>>>>> Hi Maheshakya, >>>>>>>>>>>>>>> Thank you for the resources. I will go through this and >>>>>>>>>>>>>>> looking forward to this proposed project.Thank you. >>>>>>>>>>>>>>> BR, >>>>>>>>>>>>>>> Mahesh. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> On Wed, Mar 2, 2016 at 1:52 PM, Maheshakya Wijewardena < >>>>>>>>>>>>>>> mahesha...@wso2.com> wrote: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Hi Mahesh, >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Thank you for the interest for this project. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> We would like to know what type of similar projects you >>>>>>>>>>>>>>>> have worked on. You may have seen that WSO2 Machine Learner >>>>>>>>>>>>>>>> supports >>>>>>>>>>>>>>>> several learning algorithms at the moment[1]. This project >>>>>>>>>>>>>>>> intends to >>>>>>>>>>>>>>>> leverage the existing algorithms in WSO2 Machine Learner to >>>>>>>>>>>>>>>> support >>>>>>>>>>>>>>>> streaming data. As an initiative, first you can get an idea >>>>>>>>>>>>>>>> about what WSO2 >>>>>>>>>>>>>>>> Machine Learner does and how it operates. You can download >>>>>>>>>>>>>>>> WSO2 Machine >>>>>>>>>>>>>>>> Learner from product page[2] and the the source code [3]. ML >>>>>>>>>>>>>>>> is using >>>>>>>>>>>>>>>> Apache Spark MLLib[4] for its' algorithms so it's better to >>>>>>>>>>>>>>>> read and >>>>>>>>>>>>>>>> understand what it does as well. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> In order to get an idea about the deliverables and the >>>>>>>>>>>>>>>> scope of this project, try to understand how Spark >>>>>>>>>>>>>>>> streaming[5] (see >>>>>>>>>>>>>>>> examples) handles streaming data. Also, have a look in the >>>>>>>>>>>>>>>> streaming >>>>>>>>>>>>>>>> algorithms[6][7] supported by MLLib. There are two approaches >>>>>>>>>>>>>>>> discussed to >>>>>>>>>>>>>>>> employ incremental learning in ML in the project proposals >>>>>>>>>>>>>>>> page. These >>>>>>>>>>>>>>>> streaming algorithms can be directly used in the first >>>>>>>>>>>>>>>> approach. For the >>>>>>>>>>>>>>>> other approach, the your implementation should contain a >>>>>>>>>>>>>>>> procedure to >>>>>>>>>>>>>>>> create mini batches from streaming data with relevant sizes >>>>>>>>>>>>>>>> (i.e. a moving >>>>>>>>>>>>>>>> window) and do periodic retraining of the same algorithm. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> To start with the project, you will need to come up with a >>>>>>>>>>>>>>>> suitable plan and an architecture first. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Please watch the video referenced in the proposal >>>>>>>>>>>>>>>> (reference: 5). It will help you getting a better idea about >>>>>>>>>>>>>>>> machine >>>>>>>>>>>>>>>> learning algorithms with streaming data. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Let us know if you need any help with these. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Best regards >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> [1] >>>>>>>>>>>>>>>> https://docs.wso2.com/display/ML110/Machine+Learner+Algorithms >>>>>>>>>>>>>>>> [2] http://wso2.com/products/machine-learner/ >>>>>>>>>>>>>>>> [3] >>>>>>>>>>>>>>>> https://docs.wso2.com/display/ML110/Building+from+Source#BuildingfromSource-Downloadingthesourcecheckout >>>>>>>>>>>>>>>> [4] https://spark.apache.org/docs/1.4.1/mllib-guide.html >>>>>>>>>>>>>>>> [5] >>>>>>>>>>>>>>>> https://spark.apache.org/docs/1.4.1/streaming-programming-guide.html >>>>>>>>>>>>>>>> [6] >>>>>>>>>>>>>>>> https://spark.apache.org/docs/1.4.1/mllib-linear-methods.html#streaming-linear-regression >>>>>>>>>>>>>>>> [7] >>>>>>>>>>>>>>>> https://spark.apache.org/docs/1.4.1/mllib-clustering.html#streaming-k-means >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> On Wed, Mar 2, 2016 at 1:19 PM, Mahesh Dananjaya < >>>>>>>>>>>>>>>> dananjayamah...@gmail.com> wrote: >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Hi all, >>>>>>>>>>>>>>>>> I am interesting on contribute to proposal 6: "Predictive >>>>>>>>>>>>>>>>> analytic with online data for WSO2 Machine Learner" for GSOC2 >>>>>>>>>>>>>>>>> this time. >>>>>>>>>>>>>>>>> Since i have been engaging with some similar projects i think >>>>>>>>>>>>>>>>> it will be a >>>>>>>>>>>>>>>>> great experience for me. Please let me know what you think >>>>>>>>>>>>>>>>> and what you >>>>>>>>>>>>>>>>> suggest. I have been going through your documents.thank you. >>>>>>>>>>>>>>>>> regards, >>>>>>>>>>>>>>>>> Mahesh Dananjaya. >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>>>>> Dev mailing list >>>>>>>>>>>>>>>>> Dev@wso2.org >>>>>>>>>>>>>>>>> http://wso2.org/cgi-bin/mailman/listinfo/dev >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> -- >>>>>>>>>>>>>>>> Pruthuvi Maheshakya Wijewardena >>>>>>>>>>>>>>>> mahesha...@wso2.com >>>>>>>>>>>>>>>> +94711228855 >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> -- >>>>>>>>>>>>> Pruthuvi Maheshakya Wijewardena >>>>>>>>>>>>> mahesha...@wso2.com >>>>>>>>>>>>> +94711228855 >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> -- >>>>>>>>>>> Pruthuvi Maheshakya Wijewardena >>>>>>>>>>> mahesha...@wso2.com >>>>>>>>>>> +94711228855 >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> -- >>>>>>>>> Pruthuvi Maheshakya Wijewardena >>>>>>>>> mahesha...@wso2.com >>>>>>>>> +94711228855 >>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>> >>>>>>> >>>>>>> >>>>>>> -- >>>>>>> Pruthuvi Maheshakya Wijewardena >>>>>>> mahesha...@wso2.com >>>>>>> +94711228855 >>>>>>> >>>>>>> >>>>>>> >>>>>> >>>>> >>>>> >>>>> -- >>>>> Pruthuvi Maheshakya Wijewardena >>>>> mahesha...@wso2.com >>>>> +94711228855 >>>>> >>>>> >>>>> >>>> >>> >>> >>> -- >>> Pruthuvi Maheshakya Wijewardena >>> mahesha...@wso2.com >>> +94711228855 >>> >>> >>> >> > > > -- > Pruthuvi Maheshakya Wijewardena > mahesha...@wso2.com > +94711228855 > > > -- Pruthuvi Maheshakya Wijewardena mahesha...@wso2.com +94711228855
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