Disclosed herein are techniques related to automated generation of regular expressions. In some embodiments, a regular expression generator may receive input data comprising one or more character sequences. The regular expression generator may convert character sequences into a sets of regular expression codes and/or span data structures. The regular expression generator may identify a longest common subsequence shared by the sets of regular expression codes and/or spans, and may generate a regular expression based upon the longest common subsequence.

Disclosed herein are techniques related to automated generation of regular expressions. In some embodiments, a regular expression generator may receive input data comprising one or more character sequences. The regular expression generator may convert character sequences into a sets of regular expression codes and/or span data structures. The regular expression generator may identify a longest common subsequence shared by the sets of regular expression codes and/or spans, and may generate a regular expression based upon the longest common subsequence.

A computer implemented method, computer system, and computer program product are provided for cloning a webpage. Webpage assets for a webpage are received. Using the webpage assets, the webpage is rendered for display within a graphical user interface of a webpage cloning system. Responsive to rendering the webpage, a thin-layer clone of the webpage as rendered for display in the graphical user interface is recorded. An off-line demonstration of the webpage is then generated from the thin-layer clone.

A computer implemented method, computer system, and computer program product are provided for cloning a webpage. Webpage assets for a webpage are received. Using the webpage assets, the webpage is rendered for display within a graphical user interface of a webpage cloning system. Responsive to rendering the webpage, a thin-layer clone of the webpage as rendered for display in the graphical user interface is recorded. An off-line demonstration of the webpage is then generated from the thin-layer clone.

A collection of well-formed, but possibly semantically invalid, binary encoded multimedia data components or packages as well as the binary encoded announcement, signaling, and interchange protocols used in their transmission are converted into one or more well-formed extensible markup language (XML) files. Such XML files may then be validated according to one or more pre-defined XML schemas, or similar schema languages, in order to verify that the data and protocol structures and substructures adhere to prior defined semantic constraints.

A collection of well-formed, but possibly semantically invalid, binary encoded multimedia data components or packages as well as the binary encoded announcement, signaling, and interchange protocols used in their transmission are converted into one or more well-formed extensible markup language (XML) files. Such XML files may then be validated according to one or more pre-defined XML schemas, or similar schema languages, in order to verify that the data and protocol structures and substructures adhere to prior defined semantic constraints.

A method, computer system, and a computer program product may perform document reference and reference update. One or more processors may assign marker information for a reference of a reference source. The reference may reference a target portion of a target document. The one or more processors may determine identification information for the target portion. The determined identification information may be based on content in the target portion and context information for the target portion in the target document. The one or more processors may generate a mapping of at least the marker information, the identification information, and a relative location of the target portion within the target document for use in the referencing of the target portion by the reference source.

A method, computer system, and a computer program product may perform document reference and reference update. One or more processors may assign marker information for a reference of a reference source. The reference may reference a target portion of a target document. The one or more processors may determine identification information for the target portion. The determined identification information may be based on content in the target portion and context information for the target portion in the target document. The one or more processors may generate a mapping of at least the marker information, the identification information, and a relative location of the target portion within the target document for use in the referencing of the target portion by the reference source.

Techniques are disclosed for abstractive summarization process for summarizing documents, including long documents. A document is encoded using an encoder-decoder architecture with attentive decoding. In particular, an encoder for modeling documents generates both word-level and section-level representations of a document. A discourse-aware decoder then captures the information flow from all discourse sections of a document. In order to extend the robustness of the generated summarization, a neural attention mechanism considers both word-level as well as section-level representations of a document. The neural attention mechanism may utilize a set of weights that are applied to the word-level representations and section-level representations.

Techniques are disclosed for abstractive summarization process for summarizing documents, including long documents. A document is encoded using an encoder-decoder architecture with attentive decoding. In particular, an encoder for modeling documents generates both word-level and section-level representations of a document. A discourse-aware decoder then captures the information flow from all discourse sections of a document. In order to extend the robustness of the generated summarization, a neural attention mechanism considers both word-level as well as section-level representations of a document. The neural attention mechanism may utilize a set of weights that are applied to the word-level representations and section-level representations.