Abstract: The present invention relates to methods of making certain pyrrolopyrimidine derivatives, which are useful in the treatment of proliferation disorders and other diseases related to the dysregulation of kinase (such as, but not limited to, EGFR (including HER), Alk, PDGFR, BLK, BMX/ETK, BTK, FLT3(D835Y), ITK, JAK1, JAK2, JAK3, TEC and TXK) and/or the respective pathways, salts, polymorphs, and amorphous forms of said compounds, synthetic intermediates for preparing said compounds, and pharmaceutical compositions comprising said compounds and methods for making such compositions.

Abstract: Disclosed methods of making certain pyrrolopyrimidine derivatives, which are useful in the treatment of proliferation disorders and other diseases related to the dysregulation of kinase (such as, but not limited to, EGFR (including HER), Alk, PDGFR, BLK, BMX/ETK, BTK, FLT3(D835Y), ITK, JAK1, JAK2, JAK3, TEC AND TXK) and/or the respective pathways, salts, polymorphs, and amorphous forms of said compounds, synthetic intermediates for preparing said compounds, and pharmaceutical compositions comprising said compounds and methods for making such compositions.

Abstract: Provided are methods of making certain pyrrolopyrimidine derivatives, which are useful in the treatment of proliferation disorders and other diseases related to the dysregulation of kinase (such as, but not limited to, EGFR (including HER), Alk, PDGFR, BLK, BMX/ETK, BTK, FLT3 (D835Y), ITK, JAK1, JAK2, JAK3, TEC and TXK) and/or the respective pathways, salts, polymorphs, and amorphous forms of said compounds, synthetic intermediates for preparing said compounds, and pharmaceutical compositions comprising said compounds and methods for making such compositions.

Abstract: Provided are methods of making certain pyrrolopyrimidine derivatives, which are useful in the treatment of proliferation disorders and other diseases related to the dysregulation of kinase (such as, but not limited to, EGFR (including HER), Alk, PDGFR, BLK, BMX/ETK, BTK, FLT3 (D835Y), ITK, JAK1, JAK2, JAK3, TEC and TXK) and/or the respective pathways, salts, polymorphs, and amorphous forms of said compounds, synthetic intermediates for preparing said compounds, and pharmaceutical compositions comprising said compounds and methods for making such compositions.

Abstract: Disclosed here are methods, systems, paradigms and structures for determining fraudulent content in a social network. The methods include identifying a plurality of users of the social network who perform a plurality of tasks within the social network in a lockstep manner. In the method, the plurality of users are determined to be performing a given task in the lockstep manner when the plurality of users each perform the given task within a predefined duration of time, where the predefined duration of time is associated with the given task. The method further includes identifying content data generated by the performance of the plurality of tasks by each of the plurality of users. The method further includes determining at least a portion of the content data generated by the performance of the plurality of tasks as fraudulent content.

Abstract: Disclosed here are methods, systems, paradigms and structures for determining fraudulent content in a social network. The methods include identifying a plurality of users of the social network who perform a plurality of tasks within the social network in a lockstep manner. In the method, the plurality of users are determined to be performing a given task in the lockstep manner when the plurality of users each perform the given task within a predefined duration of time, where the predefined duration of time is associated with the given task. The method further includes identifying content data generated by the performance of the plurality of tasks by each of the plurality of users. The method further includes determining at least a portion of the content data generated by the performance of the plurality of tasks as fraudulent content.

Abstract: Disclosed here are methods, systems, paradigms and structures for determining fraudulent content in a social network. The methods include identifying a plurality of users of the social network who perform a plurality of tasks within the social network in a lockstep manner. In the method, the plurality of users are determined to be performing a given task in the lockstep manner when the plurality of users each perform the given task within a predefined duration of time, where the predefined duration of time is associated with the given task. The method further includes identifying content data generated by the performance of the plurality of tasks by each of the plurality of users. The method further includes determining at least a portion of the content data generated by the performance of the plurality of tasks as fraudulent content.

Abstract: Disclosed here are methods, systems, paradigms and structures for determining fraudulent content in a social network. The methods include identifying a plurality of users of the social network who perform a plurality of tasks within the social network in a lockstep manner. In the method, the plurality of users are determined to be performing a given task in the lockstep manner when the plurality of users each perform the given task within a predefined duration of time, where the predefined duration of time is associated with the given task. The method further includes identifying content data generated by the performance of the plurality of tasks by each of the plurality of users. The method further includes determining at least a portion of the content data generated by the performance of the plurality of tasks as fraudulent content.

Abstract: Techniques to determine fake accounts of a social networking system. In one embodiment, a magnitude of a cluster of accounts is calculated. The social networking system determines the accounts are fake when the magnitude of the cluster is less than a threshold value. The accounts are not determined to be fake, or determined to be not fake, when the magnitude of the cluster is equal to or greater than the threshold value. The accounts may be associated with at least one resource. A mapping of the accounts may be created based on features associated with the accounts. A radius of the cluster is compared with the threshold value. The accounts are determined to be fake when the radius is less than the threshold value.