Searches for similar documents

A non-transitory, machine-readable medium that stores instructions, which, when performed by a machine, cause the machine to perform operations comprising:

• accessing a first document;
• identifying one or more terms from a metamodel semantic network;
• identifying one or more terms from the metamodel semantic network that are also found in the first document, wherein the identification of the one or more terms from the metamodel semantic network comprises:
• identifying a user that created the first document;
• retrieving context information associated with the user;
• identifying business functional data associated with the context information;
• identifying, from a number of domains, the domain associated with the business functional data, each domain from the number of domains including a different grouping of terms;
• and
• selecting terms that are associated with the identified domain for the analysis;
• identifying a weighted frequency of occurrence in the first document for each of the one or more identified terms, each weighted frequency of occurrence being a count of occurrences of the corresponding term in the first document multiplied by a weight based on a length of the first document;
• and
• searching for another document having one or more weighted frequencies of occurrences that are within a predefined range of a corresponding weighted frequency of occurrence of the corresponding term in the first document, the other document having been previously analyzed using terms from the identified metamodel semantic network.

A computing device comprising:

• at least one processor;
• and
• a memory in communication with the at least one processor, the memory being configured to store a similarity manager module, a text manager module, and a search engine module that are executable by the at least one processor,
• the similarity manager module having instructions that when executed by the at least one processor, cause operations to be performed, the operations comprising:
• accessing a first document;
• and identifying one or more terms from a metamodel semantic network,
• the text analyzer module having instructions that when executed by the at least one processor, cause operations to be performed, the operations comprising:
• identifying one or more terms from the metamodel semantic network that are also found in the first document, wherein the identification of the one or more terms from the metamodel semantic network comprises:
• identifying a user that created the first document;
• retrieving context information associated with the user;
• identifying business functional data associated with the context information;
• identifying, from a number of domains, the domain associated with the business functional data, each domain from the number of domains including a different grouping of terms;
• and
• selecting terms that are associated with the identified domain for the analysis;
• and
• identifying a weighted frequency of occurrence in the first document for each of the one or more identified terms, each weighted frequency of occurrence being a count of occurrences of the corresponding term in the first document multiplied by a weight based on a length of the first document, and
• the search engine module having instructions that when executed by the at least one processor, cause operations to be performed, the operations comprising searching for another document having one or more weighted frequencies of occurrences that are within a predefined range of a corresponding weighted frequency of occurrence of the corresponding term in the first document, the other document having been previously analyzed using terms from the metamodel semantic network.