Abstract: A method comprising receiving a document having multiple sections of different types using a processor. The method also comprises obtaining a plurality of lexicons using the processor, each of the lexicons for interpreting fragments in one or more of the section types. The method further comprises interpreting fragments in a first section of the multiple sections using the processor and one or more lexicons. The method still further comprises determining, based upon the interpretation and using the processor, that a fragment in the first section is misplaced. The method still further comprises re-locating, using the processor, the misplaced fragment to a second section of the multiple sections in the document to generate a re-organized document. The method additionally includes storing the re-organized document in a hardware storage system using the processor.

Abstract: A computer program product comprising a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to receive a document having multiple section headers, segment the document into at least first and second sections based on the section headers, segment items in the first section into fragments and identify a section type for each of the fragments, determine that the identified section type for at least one of the fragments better matches a type of the second section than it matches a type of the first section, and re-locate the at least one of the fragments to the second section.

Abstract: A system, comprising an input device configured to receive a first item and a second item, and a processor communicably coupled to the input device and configured to determine that the first item is a fragment matching a lexicon, and place the fragment in a section of a document, the section selected based on the matching lexicon, wherein the processor is configured to perform the determination and the placement after it receives the first item but before it receives the second item.

Abstract: Systems and methods for the semantic modeling of advertising creatives included in targeted search advertising campaigns in accordance with embodiments of the invention are disclosed. In one embodiment, an advertising creative generation device includes a processor, an advertising creative generation application, at least one semantic model and performance data, wherein the an advertising creative generation application configures the processor to obtain a set of existing advertising creatives, where at least one of the existing advertising creatives comprises an existing concept, identify at least one existing advertising strategy pattern, determine performance data for the at least one existing advertising strategy pattern based on the performance data, identify at least one performance pattern based on the performance data for the at least one existing advertising strategy pattern, and generate at least one recommended advertising strategy.

Abstract: The embodiments relate to generating hierarchical patterns based on a corpus of text. The corpus is analyzed, which includes extracting a set of features of the corpus. A set of grammatical patterns are generated based on the extracted features. The set of grammatical patterns includes at least one grammatical pattern generated from an internal pattern and at least one grammatical pattern generated from an external pattern. The grammatical patterns of the set are organized into a hierarchy and/or are ranked. The hierarchy and/or ranking are visually displayed.

Abstract: The embodiments relate to generating hierarchical patterns based on a corpus of text. The corpus is analyzed, which includes extracting a set of features of the corpus. A set of grammatical patterns are generated based on the extracted features. The set of grammatical patterns includes at least one grammatical pattern generated from an internal pattern and at least one grammatical pattern generated from an external pattern. The grammatical patterns of the set are organized into a hierarchy and/or are ranked. The hierarchy and/or ranking are visually displayed.

Abstract: Influencers (individuals or groups) over a selected audience (observers or recipients of information, objects and/or events) on a given topic are measured based on influence features, which include a sentiment flipping influence feature indicative of ability of an audience member to influence other audience members to change their sentiment on the selected topic. Other influence features include the ability to influence others: to change followership; to express interest in a topic associated with a hashtag pioneered by the influencer, based on the effectiveness and phrasing of language used. The output of the influence engine can be a score representing the relative influence of audience members over the audience on the topic of interest. Influencers may be ranked according to their total influence score over the audience on the topic.

Abstract: An approach is provided to identify important paths in a biological relationship graph for exploration by researchers. In the approach, a biological meaningfulness analysis is performed on the biological relationship graph that has a number of paths through the graph formed by a number of connected nodes. The biological meaningfulness analysis is based on a process similarity calculation of gene ontologies of the nodes in the paths and a contextual similarity calculation of word occurrences from documents in a corpus where a reference to the respective nodes are found. A biological interestingness analysis is also performed on the biological relationship graph. The paths are screened based on the meaningfulness analysis and the interestingness analysis. The screened data is displayed to the user.

Abstract: Campaign creation systems and methods for enhancing semantic models using unstructured data in accordance with embodiments of the invention are disclosed. In one embodiment, a campaign creation server system a semantic model enhancement application configuring a processor to obtain unstructured data, parse the unstructured data into parsed data, where the parsed data includes at least one piece of token data including at least one word and at least one relationship, identify at least one token not present in a semantic model, when the token is determined to be a value, identify relevant attributes within the token based on the at least one relationship in the token, when the token is determined to be a category, identify at least one parent category in the semantic model based on the at least one relationship, and update the semantic model based on the identified at least one token.

Abstract: Systems and methods for scoring phrases and keywords utilized in the generation of targeted search advertising campaigns in accordance with embodiments of the invention are disclosed. In one embodiment, a keyword and phrase scoring device includes a processor, a keyword and phrase scoring application, phrase key data, and language model performance data including category and attribute data with associated keywords and keyword performance data, wherein the keyword and phrase scoring application configures the processor to obtain a plurality of unscored keywords, identify keyword patterns in a portion of the plurality of unscored keywords, generate a keyword model based on a set of key columns, create a training language model incorporating phrase key data from the key columns using category and attribute data within the language model performance data, and score the plurality of unscored keywords based on the keyword model and the training language model.

Abstract: Exemplary embodiments of the present invention relate to a solution for the extraction of information from structured and semi-structured knowledge sources. Further, ontological relationships are inferred between the extracted information by parsing the layout structure of the structured and semi-structured knowledge sources. The inferred ontological relationships are verified in relation to existing ontological sources.