Abstract: In an example embodiment, a deep neural network is used to predict a classification for ingested job listings for a piece of information that is missing from the ingested job listings. More particularly, the deep neural network may comprise a multi-layer perceptron with a plurality of rectifier linear units (ReLUs). For a given category of information, a plurality of different information entities may be evaluated by the multi-layer perceptron against features of a job listing, producing a probability prediction of reach of those information entities for the job listing. The information entity with the highest predicted probability is identified by the multi-layer perceptron as the predicted information entity for that given category of information for the job listing.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a feature configuration for a feature. Next, the system obtains, from the feature configuration, an anchor containing metadata for accessing the feature in an environment. The system then uses one or more attributes of the anchor to retrieve one or more feature values of the feature from the environment. Finally, the system provides the one or more feature values for use with one or more machine-learning models.

Abstract: Provided is a yeast strain capable of excessively synthesizing cAMP and its construction method and fermentation technique thereof, and application in the field of medicine, animal husbandry, food or chemical industry. The yeast strain includes first and second gene modifications, wherein the first gene includes protein kinase A (PKA) catalytic subunit encoding genes TPK1, TPK2 and TPK3, by modifying the first gene, the activity or expression of PKA is completely inhibited, so that feedback inhibition to cyclic adenosine monophosphate (cAMP) is eliminated, but at the same time, the growth of the yeast is inhibited; and the second gene modification eliminates growth inhibition caused by the first gene modification, so that the yeast grows normally, and the cAMP yield by the yeast is increased, wherein the increase of the cAMP yield is relative to the cAMP yield by an unmodified yeast. The yeast strain further includes third and/or fourth gene modifications.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of records from a set of inputs, with each record containing an entity key, a partition key, and one or more attribute-value pairs. Next, the system sorts and indexes the records by the entity key for each partitioned input. The system then processes a query of the records by matching entity key values to the sorted and indexed records for each input partition in the query. Next, the system merges the subset of records with the same entity key values into records, with each merged record containing an entity key field and a single field that includes a list of attribute-value pairs from the subset. Finally, the system outputs the merged records in response to the query.

Abstract: Computer-implemented techniques for constructing structured database query language statements from natural language questions are disclosed. In some embodiments, a knowledge graph-based approach is employed to construct a structured database query language statement such as, for example, a Structure Query Language (SQL) statement, from a natural language question. The approach encompasses a domain knowledge graph model and a database schema wiring model. The domain knowledge graph model represents domain-specific knowledge about the underlying database data in the form of a graph having nodes and directed edges between the nodes. The database schema wiring model maps routes in the domain knowledge graph to database schema elements. The techniques allow a natural language interface system to accurately translate domain-specific natural language questions posed by users to structured database query language statements that can be executed against a structured database to answer the natural language question.

Abstract: Techniques of inferring an organic website URL of an organization based on a web search result are provided. A query that includes an organization name is sent to a search engine and a set of search results is received from the search engine as a result of the query. Each search result in the set of search results includes a URL for the organization website address. For each search result in the set of search results, a set of feature values that is associated with each search result is identified. The set of feature values is inputted to a prediction model that generates a prediction, and based on the prediction, a determination of whether to associate the URL of each search result with the organization name is made.

Abstract: Computer-implemented techniques for constructing structured database query language statements from natural language questions are disclosed. In some embodiments, a knowledge graph-based approach is employed to construct a structured database query language statement such as, for example, a Structure Query Language (SQL) statement, from a natural language question. The approach encompasses a domain knowledge graph model and a database schema wiring model. The domain knowledge graph model represents domain-specific knowledge about the underlying database data in the form of a graph having nodes and directed edges between the nodes. The database schema wiring model maps routes in the domain knowledge graph to database schema elements. The techniques allow a natural language interface system to accurately translate domain-specific natural language questions posed by users to structured database query language statements that can be executed against a structured database to answer the natural language question.

Abstract: Provided is a yeast strain capable of excessively synthesizing cAMP and its construction method and fermentation technique thereof, and application in the field of medicine, animal husbandry, food or chemical industry. The yeast strain includes first and second gene modifications, wherein the first gene includes protein kinase A (PKA) catalytic subunit encoding genes TPK1, TPK2 and TPK3, by modifying the first gene, the activity or expression of PKA is completely inhibited, so that feedback inhibition to cyclic adenosine monophosphate (cAMP) is eliminated, but at the same time, the growth of the yeast is inhibited; and the second gene modification eliminates growth inhibition caused by the first gene modification, so that the yeast grows normally, and the cAMP yield by the yeast is increased, wherein the increase of the cAMP yield is relative to the cAMP yield by an unmodified yeast. The yeast strain further includes third and/or fourth gene modifications.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a feature configuration for a feature. Next, the system obtains, from the feature configuration, an anchor containing metadata for accessing the feature in an environment. The system then uses one or more attributes of the anchor to retrieve one or more feature values of the feature from the environment. Finally, the system provides the one or more feature values for use with one or more machine-learning models.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of features for use with one or more statistical models. Next, the system generates feature profiling data containing a set of statistics for the set of features. The system then outputs the feature profiling data for use in characterizing a distribution of the features. Furthermore, the system updates the outputted feature profiling data based on a granularity associated with the statistics. Finally, the system uses the statistics in the feature profiling data to perform anomaly detection and alerts users if unexpected feature distribution change is detected.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of features for use by a set of statistical models. Next, the system generates a schema that includes a logical description of data represented by the features and a physical description related to generating and storing the features. The system then outputs the schema for use in managing and sharing the features across the statistical models. Finally, the system updates the outputted schema to reflect one or more parameters from a user.

Abstract: Methods, systems, and computer programs are presented for selecting a title for a post of a social network. A method includes operations for identifying a word weight for each word in a corpus based on the relevance of each word, receiving a document that includes several sentences, and assigning to each word in the sentences a tag indicative of a part of speech. Further, the method includes operations for calculating a topic weight for each sentence based on the tags of the words in the sentence, and for calculating a sentence weight for each sentence based on a sum of the word weights of the words in the sentence, the topic weight for the sentence, and a position weight of the sentence within a paragraph. The sentence with the highest sentence weight is selected as the title for the document, and the title is presented with the document to a user.

Abstract: Methods, systems, and computer programs are presented for selecting a title for a post of a social network. A method includes operations for identifying a word weight for each word in a corpus based on the relevance of each word, receiving a document that includes several sentences, and assigning to each word in the sentences a tag indicative of a part of speech. Further, the method includes operations for calculating a topic weight for each sentence based on the tags of the words in the sentence, and for calculating a sentence weight for each sentence based on a sum of the word weights of the words in the sentence, the topic weight for the sentence, and a position weight of the sentence within a paragraph. The sentence with the highest sentence weight is selected as the title for the document, and the title is presented with the document to a user.

Abstract: The disclosed embodiments provide a system for processing textual content. During operation, the system obtains a content item containing a set of text units. For each text unit in the set of text units, the system obtains a similarity score representing a similarity of the text unit to other text units in the content item and calculates a ranking score for the text unit from a combination comprising a text unit frequency for the text unit, the similarity score, and a position weight associated with a position of the text unit in the content item. The system then ranks the set of text units by the ranking score and uses the ranking to display a summary containing a subset of the text units in the content item.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of records from a set of inputs, with each record containing an entity key, a partition key, and one or more attribute-value pairs. Next, the system sorts and indexes the records by the entity key for each partitioned input. The system then processes a query of the records by matching entity key values to the sorted and indexed records for each input partition in the query. Next, the system merges the subset of records with the same entity key values into records, with each merged record containing an entity key field and a single field that includes a list of attribute-value pairs from the subset. Finally, the system outputs the merged records in response to the query.