A method for generating hypotheses in a corpus of data comprises selecting a form of ontology; coding the corpus of data based on the form of the ontology; generating ontology space based on coding results and the ontology; transforming the ontology space into a hypothesis space by grouping hypotheses; weighing hypotheses included in the hypothesis space; and applying a science-based optimization algorithm configured to model a science-based treatment of the weighted hypotheses.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of generating hypotheses from data, comprising: constructing an ontology space including a plurality of ontology nodes by extracting elements from the data; transforming the ontology space to a hypothesis space including a plurality of hypotheses nodes; applying a weighted schema to the hypothesis space in order to set relevancy criteria; and solving an optimization problem using the hypothesis space with the weighting applied. 2. The method of claim 1, wherein constructing the ontology space comprises parsing documents included in the data to detect events, and assigning the events in the documents to the ontology nodes. 3. The method of claim 1, wherein the events are subject, verb, object tuples and constructing the ontology space comprises grouping the subject, verb, object tuples so as to create sets of distinct combinations. 4. The method of claim 1, wherein transforming the ontology space into the hypothesis space comprises grouping and merging related topics. 5. The method of claim 4, further comprising filtering the ontology space based on relevance to a user. 6. The method of claim 1, wherein the transforming of the ontology space comprises merging the ontology nodes using one of the following: a clustering technique, a filter, a topic model, a conditional random field. 7. The method of claim 1, wherein applying the weighted schema comprises using a simulated annealing representation or a genetic algorithm representation. 8. The method of claim 1, wherein applying the weighted schema comprises one or more of the following techniques: analyzing word frequency, analyzing parts of speech, or excluding nodes that are not of interest. 9. The method of claim 1, further including devaluing hypotheses nodes corresponding to uninteresting hypotheses nodes using a weighting. 10. The method of claim 1, wherein the applying of the weighted schema comprises ranking the hypotheses nodes. 11. The method of claim 1, wherein solving the optimization problem comprises using simulated annealing, a genetic algorithm, Monte Carlo methods, a topological optimization method, or a statistical optimization method. 12. A method of generating hypotheses, comprising: collecting data from one or more sources; constructing an ontology space by extracting elements from the data and generating a cross product of distinct elements so as to include a plurality of hypotheses; transforming the ontology space to a hypothesis space by grouping and merging hypotheses that have an associated metric in common; filtering the hypothesis space to reduce a number of hypotheses, wherein the filtering is based on relevance of the hypotheses to a user; and generating a ranking of the hypotheses based on relevance. 13. The method of claim 12, wherein the generating of the ranking comprises applying a weighted schema to the hypothesis space. 14. The method of claim 12, wherein the generating of the ranking comprises performing a plurality of simulated annealing runs and determining the hypotheses that are most frequently used. 15. The method of claim 12, wherein constructing the ontology space comprises parsing documents included in the data to find ontological combinations. 16. The method of claim 15, wherein the ontological combinations include a subject, verb, and object ontology. 17. The method of claim 15, wherein filtering the hypothesis space comprises reading a user profile from memory and using the user profile to determine hypotheses that are of interest to the user. 18. A computer-readable storage medium including instructions that upon execution cause a computer system to perform the following method, comprising; collecting data from one or more sources; construct an ontology space including a plurality of ontology nodes by extracting elements from the data; transform the ontology space to a hypothesis space including a plurality of hypotheses nodes; apply a weighted schema to the hypothesis space in order to set relevancy criteria; and solve an optimization problem using the hypothesis space with the weighting applied. 19. The computer-readable storage medium of claim 18, further including filtering the hypothesis space to reduce a number of nodes used in the hypothesis space. 20. The computer-readable storage medium of claim 19, wherein the filtering is based on a user profile.