A method is provided for converting a binary data stream, (e.g., an EXI data stream). In an initialization phase of the method, a plurality of grammars, previously produced from at least one description language scheme, are read from a memory area and combined to form a combined grammar and wherein the combined grammar is supplied to a runtime environment for the purpose of converting the binary data stream. The method firstly permits substantially accelerated production of the desired grammar in comparison with a grammar produced as required from individual schemes, and secondly the memory space requirement may be kept down, because there is no need to keep a combinational variety of grammars available.

Methods, systems, and non-transitory media for training a chemical entity recognition system to extract chemical compounds from a patent document and determine a relevance of the chemical compounds to the patent document are disclosed. A method includes obtaining patent documents from patent databases, normalizing each patent document into a unified format, and generating a chemical patent corpus. The chemical patent corpus includes chemical entities, each having relevancy annotations that indicate a relevance to the patent document from which the chemical entity is extracted. The method further includes providing the chemical patent corpus to the chemical entity recognition system, which tags the one or more chemical entities in a corresponding normalized patent document, extracts additional chemical entities, assigns a confidence score to each additional chemical entity, and labels each additional chemical entity as relevant or irrelevant to an associated patent document based on information contained in the chemical patent corpus.

Methods, systems, and non-transitory media for training a chemical entity recognition system to extract chemical compounds from a patent document and determine a relevance of the chemical compounds to the patent document are disclosed. A method includes obtaining patent documents from patent databases, normalizing each patent document into a unified format, and generating a chemical patent corpus. The chemical patent corpus includes chemical entities, each having relevancy annotations that indicate a relevance to the patent document from which the chemical entity is extracted. The method further includes providing the chemical patent corpus to the chemical entity recognition system, which tags the one or more chemical entities in a corresponding normalized patent document, extracts additional chemical entities, assigns a confidence score to each additional chemical entity, and labels each additional chemical entity as relevant or irrelevant to an associated patent document based on information contained in the chemical patent corpus.

Systems, methods, and other embodiments associated with self-transformation objects are described. In one embodiment, a method includes determining that a content object is to be rendered. The example method may also include evaluating attributes of a user to identify a content preference of the user. The example method may also include identifying a content transformation mapping that corresponds to the content preference. The example method may also include parsing the content object to identify a transformation script. The example method may also include executing the transformation script to parse the content object to identify elements that are tagged with a transformation tag. The example method may also include executing the transformation script to apply corresponding transformations from the content transformation mapping to the tagged elements. The example method may also include rendering the content object with the transformed elements.

Systems, methods, and other embodiments associated with self-transformation objects are described. In one embodiment, a method includes determining that a content object is to be rendered. The example method may also include evaluating attributes of a user to identify a content preference of the user. The example method may also include identifying a content transformation mapping that corresponds to the content preference. The example method may also include parsing the content object to identify a transformation script. The example method may also include executing the transformation script to parse the content object to identify elements that are tagged with a transformation tag. The example method may also include executing the transformation script to apply corresponding transformations from the content transformation mapping to the tagged elements. The example method may also include rendering the content object with the transformed elements.

A text stream source is accessed that includes a plurality of text content items. Unique word groupings are determined for the plurality of text content items. A burst detection algorithm is executed to determine word groupings that are currently bursting and that started within a specified time period. Based on the word groupings, an issue is determined based on identifying a set of texts forming at least one clique.

A text stream source is accessed that includes a plurality of text content items. Unique word groupings are determined for the plurality of text content items. A burst detection algorithm is executed to determine word groupings that are currently bursting and that started within a specified time period. Based on the word groupings, an issue is determined based on identifying a set of texts forming at least one clique.

A method for sharing content is provided. An image of content is obtained. An address is generated based on the image using a set of predefined rules. The address is associated with the content. The content is provided to a computing device in response to the computing device accessing the address.

A method for sharing content is provided. An image of content is obtained. An address is generated based on the image using a set of predefined rules. The address is associated with the content. The content is provided to a computing device in response to the computing device accessing the address.

Data is organized in a hierarchical data tree having nodes, and is formatted in human-readable data according to a schema. The data is canonically ordered in correspondence with a canonical ordering of a schema dictionary generated from the schema. The canonically ordered data is encoded into binary, including for each node, removing a label of the node, and adding a sequence number of the node corresponding to the canonical ordering, in binary.