Abstract: An approach is provided in which identifying a plurality of sections included in a Portable Document Format (PDF) file with each section being at a unique set of coordinate positions. At least one of the sections is identified as being a graphic image. The graphic image section is converted to a meaningful textual representations using a conversion process. An output document is then generated that includes the meaningful textual representation.

Abstract: A semantic search engine is enhanced to employ user preferences to customize answer output by, for a first user, extracting user preferences and sentiment levels associated with a first question; receiving candidate answer results of a semantic search of the first question; weighting the candidate answer results according to the sentiment levels for each of the user preferences; and producing the selected candidate answers to the first user. Optionally, user preferences and sentiment levels may be accumulated over different questions for the same user, or over different users for similar questions. And, supplemental information may be retrieved relative to a user preference in order to further tune the weighting per the preferences and sentiment levels.

Abstract: A semantic search engine is enhanced to employ user preferences to customize answer output by, for a first user, extracting user preferences and sentiment levels associated with a first question; receiving candidate answer results of a semantic search of the first question; weighting the candidate answer results according to the sentiment levels for each of the user preferences; and producing the selected candidate answers to the first user. Optionally, user preferences and sentiment levels may be accumulated over different questions for the same user, or over different users for similar questions. And, supplemental information may be retrieved relative to a user preference in order to further tune the weighting per the preferences and sentiment levels.

Abstract: Methods, apparatus and systems, including computer program products, for creating subject matter synonyms from definitions extracted from a subject matter glossary. Confidence scores, each representing a likelihood that two terms defined in the subject matter glossary are synonyms, are determined by applying natural language processing (e.g., passage term matching, lexical matching, and syntactic matching) to the extracted definitions. A subject matter thesaurus is built based on the confidence scores. In one embodiment, a statement containing a first term is created based on an extracted definition of the first term, a modified statement is created by substituting a second term in the statement in lieu of the first term, a corpus is searched, and a confidence score is determined based on evidence in the corpus that the modified statement is accurate. The first and second terms are marked as synonyms if the confidence score is greater than a threshold.

Abstract: A semantic search engine is enhanced to employ user preferences to customize answer output by, for a first user, extracting user preferences and sentiment levels associated with a first question; receiving candidate answer results of a semantic search of the first question; weighting the candidate answer results according to the sentiment levels for each of the user preferences; and producing the selected candidate answers to the first user. Optionally, user preferences and sentiment levels may be accumulated over different questions for the same user, or over different users for similar questions. And, supplemental information may be retrieved relative to a user preference in order to further tune the weighting per the preferences and sentiment levels.

Abstract: Mechanisms are provided for performing tabular data correction in a document. Tabular data is received and analyzed to identify at least one portion of the tabular data having an erroneous/missing data value. A functional dependency of the at least one portion of the tabular data on one or more other portions of the tabular data is determined. A correct data value for the erroneous or missing data value of the at least one portion of the tabular data is determined based on the functional dependency of the at least one portion. In addition, the tabular data is modified to replace the erroneous or missing data value with the correct data value and thereby generate a modified table data. A processing operation is then performed on the modified table data to generate a resulting output.

Abstract: A table structure corresponding to the table is selected to describe when cells in a cell-pair in the table structure should be similar to one another. A cell similarity function is selected to compare the cells in the cell-pair and output a probability that the cell-pair includes cells that contain values that are similar to one another according to a criteria. A cell similarity probability is determined of a first cell and a second cell in a first cell-pair in the table structure being similar to each other according to the cell similarity function. A computed probability is adjusted of the table structure representing the table using the cell similarity probability. The computed probability is indicated as a probability of a first model representing the table, wherein the first model is a function of the table structure and the selected cell similarity function.

Abstract: A table structure corresponding to the table is selected to describe when cells in a cell-pair in the table structure should be similar to one another. A cell similarity function is selected to compare the cells in the cell-pair and output a probability that the cell-pair includes cells that contain values that are similar to one another according to a criteria. A cell similarity probability is determined of a first cell and a second cell in a first cell-pair in the table structure being similar to each other according to the cell similarity function. A computed probability is adjusted of the table structure representing the table using the cell similarity probability. The computed probability is indicated as a probability of a first model representing the table, wherein the first model is a function of the table structure and the selected cell similarity function.

Abstract: Embodiments of the present invention provide a method, system and computer program product for the on-demand generation of correlated collections of mashable data from distributed, heterogeneous data sources. In an embodiment of the invention, a method for on-demand generation of correlated collections of mashable data from distributed, heterogeneous data sources is provided. The method includes receiving a request for a data feed from a widget in a mashup rendered in a content browser executing in memory of a computer. The method further includes inspecting a virtual database of data aggregated from different data sources over a computer communications network to locate data requisite to returning the data feed to the widget in the mashup. The method yet further includes querying the data of the virtual database to produce the data feed. Finally, the method includes returning the data feed in the format specified to the widget in the mashup.

Abstract: A visualization of literary elements of a work of literature, such as a novel or short story, is generated from meta-data records representing a digital work of literature including literary elements (humor, drama, adventure, etc.), characters, and plot devices related to a position within the work of literature where each appears. A significance level is determined for each of the elements, characters and plot devices at each position within the work of literature, and these are plotted into a sequential graph having position (e.g. timeline) axis and a significance level axis. The sequential graph is then output for printing or display. Human-generated and machine-generated meta-data may be ingested equally well by the method. Colors, line thickness, and a broken line patterns may be employed for greater visual meaning. And, the sequential graph may be annotated according to segments (e.g. chapters, sections) and dominant genre within each segment.

Abstract: Methods, apparatus and systems, including computer program products, for creating subject matter synonyms from definitions extracted from a subject matter glossary. Confidence scores, each representing a likelihood that two terms defined in the subject matter glossary are synonyms, are determined by applying natural language processing (e.g., passage term matching, lexical matching, and syntactic matching) to the extracted definitions. A subject matter thesaurus is built based on the confidence scores. In one embodiment, a statement containing a first term is created based on an extracted definition of the first term, a modified statement is created by substituting a second term in the statement in lieu of the first term, a corpus is searched, and a confidence score is determined based on evidence in the corpus that the modified statement is accurate. The first and second terms are marked as synonyms if the confidence score is greater than a threshold.

Abstract: Mechanisms are provided for performing tabular data correction in a document. Tabular data is received and analyzed to identify at least one portion of the tabular data having an erroneous/missing data value. A functional dependency of the at least one portion of the tabular data on one or more other portions of the tabular data is determined. A correct data value for the erroneous or missing data value of the at least one portion of the tabular data is determined based on the functional dependency of the at least one portion. In addition, the tabular data is modified to replace the erroneous or missing data value with the correct data value and thereby generate a modified table data. A processing operation is then performed on the modified table data to generate a resulting output.

Abstract: A system, and computer program product for subject-matter analysis of tabular data are provided in the illustrative embodiments. A first document including the tabular data is received. A library of functional signatures for a first subject-matter domain is selected. A determination is made whether a threshold number of functional signatures from the selected library are applicable to the tabular data, wherein a functional signature is applicable to the tabular data when values in the tabular data correspond to an operation and a table structure specified in the functional signature. Responsive to the threshold number of functional signatures from the selected library being applicable to the tabular data, a processor and a memory process the first document according to a process for the first subject matter domain selected from a plurality of processes for respective subject matter domains.

Abstract: A method for subject-matter analysis of tabular data is provided in the illustrative embodiments. A first document including the tabular data is received. A library of functional signatures for a first subject-matter domain is selected. A determination is made whether a threshold number of functional signatures from the selected library are applicable to the tabular data, wherein a functional signature is applicable to the tabular data when values in the tabular data correspond to an operation and a table structure specified in the functional signature. Responsive to the threshold number of functional signatures from the selected library being applicable to the tabular data, a processor and a memory process the first document according to a process for the first subject matter domain selected from a plurality of processes for respective subject matter domains.

Abstract: A semantic search engine is enhanced to employ user preferences to customize answer output by, for a first user, extracting user preferences and sentiment levels associated with a first question; receiving candidate answer results of a semantic search of the first question; weighting the candidate answer results according to the sentiment levels for each of the user preferences; and producing the selected candidate answers to the first user. Optionally, user preferences and sentiment levels may be accumulated over different questions for the same user, or over different users for similar questions. And, supplemental information may be retrieved relative to a user preference in order to further tune the weighting per the preferences and sentiment levels.

Abstract: A method for discovering relationships in tabular data is provided in the illustrative embodiments. A set of documents is received, a document in the set including the tabular data. A cell in the tabular data is selected whose dependencies are to be determined. A hypothesis to use in conjunction with the cell is selected. Whether the hypothesis applies to a selected portion of the document is tested by determining whether a conclusion in the hypothesis can be computed using a function specified in the hypothesis on the selected portion. The selected portion can be a selected cell-range in the tabular data or content in a non-tabular portion of the document. The hypothesis is utilized to describe the cell relative to the selected portion.

Abstract: A system, and computer program product for discovering relationships in tabular data are provided in the illustrative embodiments. A set of documents is received, a document in the set including the tabular data. A cell in the tabular data is selected whose dependencies are to be determined. A hypothesis to use in conjunction with the cell is selected. Whether the hypothesis applies to a selected portion of the document is tested by determining whether a conclusion in the hypothesis can be computed using a function specified in the hypothesis on the selected portion. The selected portion can be a selected cell-range in the tabular data or content in a non-tabular portion of the document. The hypothesis is utilized to describe the cell relative to the selected portion.

Abstract: Mechanisms are provided for performing tabular data correction in a document. Tabular data is received and analyzed to identify at least one portion of the tabular data having an erroneous/missing data value. A functional dependency of the at least one portion of the tabular data on one or more other portions of the tabular data is determined. A correct data value for the erroneous or missing data value of the at least one portion of the tabular data is determined based on the functional dependency of the at least one portion. In addition, the tabular data is modified to replace the erroneous or missing data value with the correct data value and thereby generate a modified table data. A processing operation is then performed on the modified table data to generate a resulting output.

Abstract: Mechanisms, in a data processing system, are provided for extracting semantic relationships amongst table contents in a table data structure associated with an electronic document. These mechanisms determine a configuration of cells within the table data structure. The mechanisms identify one or more super-cells within the table data structure based on the determined configuration of cells. The mechanisms also, for each super-cell in the one or more super-cells, converts table data corresponding to the super-cell into a semantic relationship statement for the super-cell, wherein the semantic relationship statement identifies one or more relationships between portions of the table data corresponding to the super-cell. The mechanisms further store the semantic relationship statements for each of the super-cells in association with the table data structure.

Abstract: A semantic search engine is enhanced to employ user preferences to customize answer output by, for a first user, extracting user preferences and sentiment levels associated with a first question; receiving candidate answer results of a semantic search of the first question; weighting the candidate answer results according to the sentiment levels for each of the user preferences; and producing the selected candidate answers to the first user. Optionally, user preferences and sentiment levels may be accumulated over different questions for the same user, or over different users for similar questions. And, supplemental information may be retrieved relative to a user preference in order to further tune the weighting per the preferences and sentiment levels.