The present invention relates generally to identifying relationships between items. Certain embodiments of the present invention are configurable to identify the probability that a certain event will occur by identifying relationships between items. Certain embodiments of the present invention provide an improved supervised machine learning system.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system for automatically generating quality hypotheses, comprising: a processor: a main memory in communication with said processor via a communication infrastructure and storing instructions that, when executed by said processor, cause the processor to: access a collection including at least two or more information items; develop a training set from the at least two or more information items in the collection; analyze the training set; produce a classifier element; establish an evaluation set of information items; apply the classifier element to the evaluation set; and deliver an output regarding likelihood of interaction between the information items in the evaluation set, thereby identifying experiments likely to provide positive information, and thereby generate quality hypotheses. 2. The system of claim 1, wherein one of the at least two or more information items is a type of protein. 3. The system of claim 2, wherein one of the at least two or more information items is a publication. 4. The system of claim 1, wherein one of the at least two or more information items is a type of pharmaceutical drug. 5. The system of claim 1, wherein the analyze step includes extracting one or more features from the training set. 6. The system of claim 5, wherein one of the at least one or more features is a first publication date of a publication. 7. The system of claim 5, wherein one of the at least one or more features is authorship of a publication. 8. The system of claim 7, wherein one of the at least one or more features is co-authorship of two or more publications. 9. The system of claim 5, wherein one of the at least one or more features is an identification tag of a publication. 10. A system of claim 1, wherein said main memory in communication with the processor via the communication infrastructure stores instructions that, when executed by said processor, cause said processor to display a graphical representation configured to convey at least known relationships between information items. 11. The system of claim 10, wherein the graphical representation includes a node symbol configured to represent the information item and a link symbol configured to represent any relationships between the information items. 12. The system of claim 11, wherein a degree may be calculated for the node symbol. 13. A system of claim 1, wherein said main memory in communication with said processor via the communication infrastructure stores instructions that, when executed by said processor, cause said processor to display a graphical representation configured to convey predicted relationships between the information items. 14. A system of claim 1, wherein said main memory in communication with said processor via the communication infrastructure stores instructions that, when executed by said processor, cause said processor to rank the output regarding likelihood of interaction between certain of the at least two or more information items in the evaluation set to facilitate easy identification of the at least or more information items that are most likely to interact. 15. A system for automatically generating quality hypotheses, comprising: a processor; a main memory in communication with said processor via a communication infrastructure and storing instructions that, when executed by said processor, cause the processor to: form a collection including at least two or more information items; develop a training set from the at least two or more information items in the collection; analyze the training set; produce a classifier element; establish an evaluation set of information items; apply the classifier element to the evaluation set; and deliver an output regarding likelihood of interaction between the at least two or more information items in the evaluation set, thereby identifying experiments likely to provide positive information, and thereby generate quality hypotheses. 16. The system of claim 15, wherein the training set is indexed to facilitate analysis of the training set. 17. The system of claim 15, wherein the evaluation set is indexed to facilitate analysis of the evaluation set. 18. The system of claim 15, wherein one of the at least two or more information items is a protein. 19. The system of claim 15, wherein one of the at least two or more information items is a publication. 20. The system of claim 15, wherein one of the at least two or more information items is a type of pharmaceutical drug.