Abstract: Disclosed is a tea leaf and tea stem separating device. The tea leaf and tea stem separating device comprises a machine shell, wherein a collecting mechanism, a peeling mechanism, a separating mechanism, a rocker mechanism and recycling mechanisms are sequentially arranged on the machine shell in the falling direction of materials, a driving mechanism is arranged at the position, corresponding to the separating mechanism, of the inner wall of the machine shell, the driving mechanism is provided with a conveyor belt mechanism connected with the peeling mechanism, the separating mechanism and the rocker mechanism, and the driving mechanism can drive the conveyor belt mechanism to move so as to pull the peeling mechanism, the separating mechanism and the rocker mechanism to synchronously reciprocate.

Abstract: A computer-implemented method, system and computer program product for providing predictions tailored for a specific domain. Each field within a set of datasets is classified with a concept defined in a domain specific ontology. After receiving a target field and identifying a target concept tagged to the target field, concepts that have an influential impact directly to the target concept or indirectly to a concept tagged to a field associated with the target field are identified. Fields are then identified as candidates for predictors from the identified concepts using a semantic relationship and a numeric association combined approach. An influential confidence score and a numeric analytics score are then calculated for each of these candidates upon which a final confidence score is computed. The identified candidates are ranked based on the final confidence scores, and the top ranked candidates for predictors are selected to build a statistical model.

Abstract: Disclosed is a tea leaf and tea stem separating device. The tea leaf and tea stem separating device comprises a machine shell, wherein a collecting mechanism, a peeling mechanism, a separating mechanism, a rocker mechanism and recycling mechanisms are sequentially arranged on the machine shell in the falling direction of materials, a driving mechanism is arranged at the position, corresponding to the separating mechanism, of the inner wall of the machine shell, the driving mechanism is provided with a conveyor belt mechanism connected with the peeling mechanism, the separating mechanism and the rocker mechanism, and the driving mechanism can drive the conveyor belt mechanism to move so as to pull the peeling mechanism, the separating mechanism and the rocker mechanism to synchronously reciprocate.

Abstract: A computer-implemented method, a computer program product, and a computer system for identifying an influencer combination having a root cause to a key performance indicator change. The computer system analyzes metadata to discover semantic information for each column of data, identifies candidate factors that categorize a target performance indicators (KPI), groups the candidate factors into groups based on hierarchies which are included in the semantic information. For respective ones of the hierarchies, the computer system chooses most influential levels as influencer candidates. The computer system creates a stratified sample based on a distribution of target KPI values and evaluates an influential strength to the target KPI. The computer system identifies top influencers in the influencer candidates, based on influential strengths of respective ones of the influencer candidates.

Abstract: A computer-implemented method, system, and computer program product for generating a semantic model of data comprising a plurality of data items. Semantic concepts are identified for each data item in the plurality of data items. Data concepts are identified for each data item in the plurality of data items based on data characteristics of the data item and using a data ontology that defines the data concepts that are used to represent the data characteristics. The semantic model of the data is generated using the semantic concepts and the data concepts identified for the plurality of data items.

Abstract: A computer-implemented method for joining data sets with mismatched geographic location naming conventions is provided. The method includes identifying, by the computer, a first dataset and a second dataset as join candidates. The method also includes joining, by the computer, the first dataset and the second dataset when, each row of the first user dataset is associated with a single geographic identifier using a geographic knowledge dataset that includes a geographic name lookup table and each row of the second user dataset is associated with a single geographic identifier using the geographic knowledge dataset, wherein the geographic name lookup table includes a plurality of alias names for each of a plurality of unique geographic locations.

Abstract: Some embodiments include a method for identifying named entities in a question received in a question and answer system. The method can include receiving the question and constructing, via a named entity controller, a search query using all words in the question. The method can also include searching a named entity index for records that include named entity fields associated with certain of the words in the question. The method can also include determining a search score for each of the records based, at least in part, on how closely words in the question match a field of the record. The method can also include determining a weighted score for each of the records based on where the words in the question are positioned in the question. The method can also include creating a list of records including one or more of the records whose weighted score is above a threshold score. The method can also include providing the list of records for use in answering questions in the question and answer system.

Abstract: A big data analytics system includes an event monitoring controller that detects a user targeted event from an initial digital query data flow. An event conversion controller determines at least one contextual element associated with the at least one user targeted event, and automatically converts the at least one contextual element into a search criteria. An external data query builder controller automatically executes an external search query based on the search criteria. A data fusing controller automatically fuses the at least one contextual element generated from the at least one user targeted event, together with external search results generated from the external search query and the initial query data flow to generate a fused data file.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: metadata on respective datasets from a plurality of data sources. An enhanced metadata is prepared with semantic information, available data statistics, and search index associated with items of the metadata. The metadata is also classified based on ontology rules. An intent phrase to search the datasets from the plurality of data sources is obtained from a user. The enhanced metadata is searched with a semantic search query formed from the intent phrase, and search result is classified into semantic element classes generated from the intent phrase. A metadata model that satisfies the intent phrase is produced by identifying join columns and respective join relationships from the search result.

Abstract: A computer-implemented method for joining data sets with mismatched geographic location naming conventions is provided. The method includes identifying, by the computer, a first dataset and a second dataset as join candidates. The method also includes joining, by the computer, the first dataset and the second dataset when, each row of the first user dataset is associated with a single geographic identifier using a geographic knowledge dataset that includes a geographic name lookup table and each row of the second user dataset is associated with a single geographic identifier using the geographic knowledge dataset, wherein the geographic name lookup table includes a plurality of alias names for each of a plurality of unique geographic locations.

Abstract: A computer-implemented method, system, and computer program product for classifying a concept of a data item. A data item label for the data item is received. The data item label is analyzed using a natural language processing tool to generate additional lexical information for the data item label. A search query is built using the additional lexical information for the data item label. The search query is used to search a clue concept index to produce a search result. The clue concept index comprises clue concept records that identify clues for concepts. The search result identifies clue concept records from the clue concept index that match the search query. A concept is selected from the clue concept records identified in the search result as the concept for the data item.

Abstract: A computer-implemented method, system and computer program product for providing predictions tailored for a specific domain. Each field within a set of datasets is classified with a concept defined in a domain specific ontology. After receiving a target field and identifying a target concept tagged to the target field, concepts that have an influential impact directly to the target concept or indirectly to a concept tagged to a field associated with the target field are identified. Fields are then identified as candidates for predictors from the identified concepts using a semantic relationship and a numeric association combined approach. An influential confidence score and a numeric analytics score are then calculated for each of these candidates upon which a final confidence score is computed. The identified candidates are ranked based on the final confidence scores, and the top ranked candidates for predictors are selected to build a statistical model.

Abstract: A computer-implemented method, system, and computer program product for generating a semantic model of data comprising a plurality of data items. Semantic concepts are identified for each data item in the plurality of data items. Data concepts are identified for each data item in the plurality of data items based on data characteristics of the data item and using a data ontology that defines the data concepts that are used to represent the data characteristics. The semantic model of the data is generated using the semantic concepts and the data concepts identified for the plurality of data items.

Abstract: A computer-implemented method, system, and computer program product for classifying a concept of a data item. A data item label for the data item is received. The data item label is analyzed using a natural language processing tool to generate additional lexical information for the data item label. A search query is built using the additional lexical information for the data item label. The search query is used to search a clue concept index to produce a search result. The clue concept index comprises clue concept records that identify clues for concepts. The search result identifies clue concept records from the clue concept index that match the search query. A concept is selected from the clue concept records identified in the search result as the concept for the data item.

Abstract: A big data analytics system includes an event monitoring controller that detects a user targeted event from an initial digital query data flow. An event conversion controller determines at least one contextual element associated with the at least one user targeted event, and automatically converts the at least one contextual element into a search criteria. An external data query builder controller automatically executes an external search query based on the search criteria. A data fusing controller automatically fuses the at least one contextual element generated from the at least one user targeted event, together with external search results generated from the external search query and the initial query data flow to generate a fused data file.

Abstract: A mechanism is provided for advanced search-term disambiguation. Responsive to detecting a search term being entered into an autocomplete search field of a search engine, a determination is made of a set of terms from a storage device upon which a search is to be performed. For each term in the set of terms, a determination is made of a semantic distance and independence (Sdi) score to each term candidate in a set of term candidates. The results of the semantic distance and independence (Sdi) scores are ranked and then pruned down to a predetermined number of autocomplete results. A subset of term candidates associated with the predetermined number of autocomplete results from the set of term candidates is then presented to a user as autocomplete suggestions to the search.

Abstract: Some embodiments include a method for identifying named entities in a question received in a question and answer system. The method can include receiving the question and constructing, via a named entity controller, a search query using all words in the question. The method can also include searching a named entity index for records that include named entity fields associated with certain of the words in the question. The method can also include determining a search score for each of the records based, at least in part, on how closely words in the question match a field of the record. The method can also include determining a weighted score for each of the records based on where the words in the question are positioned in the question. The method can also include creating a list of records including one or more of the records whose weighted score is above a threshold score. The method can also include providing the list of records for use in answering questions in the question and answer system.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: metadata on respective datasets from a plurality of data sources. An enhanced metadata is prepared with semantic information, available data statistics, and search index associated with items of the metadata. The metadata is also classified based on ontology rules. An intent phrase to search the datasets from the plurality of data sources is obtained from a user. The enhanced metadata is searched with a semantic search query formed from the intent phrase, and search result is classified into semantic element classes generated from the intent phrase. A metadata model that satisfies the intent phrase is produced by identifying join columns and respective join relationships from the search result.

Abstract: A mechanism is provided for advanced search-term disambiguation. Responsive to detecting a search term being entered into an autocomplete search field of a search engine, a determination is made of a set of terms from a storage device upon which a search is to be performed. For each term in the set of terms, a determination is made of a semantic distance and independence (Sdi) score to each term candidate in a set of term candidates. The results of the semantic distance and independence (Sdi) scores are ranked and then pruned down to a predetermined number of autocomplete results. A subset of term candidates associated with the predetermined number of autocomplete results from the set of term candidates is then presented to a user as autocomplete suggestions to the search.

Abstract: A big data analytics system includes an event monitoring controller that detects a user targeted event from an initial digital query data flow. An event conversion controller determines at least one contextual element associated with the at least one user targeted event, and automatically converts the at least one contextual element into a search criteria. An external data query builder controller automatically executes an external search query based on the search criteria. A data fusing controller automatically fuses the at least one contextual element generated from the at least one user targeted event, together with external search results generated from the external search query and the initial query data flow to generate a fused data file.