Systems, methods, and software for hyperlinking names
First Claim
1. A computer-implemented method comprising:
- identifying a name in a document;
determining a rarity indicator for the name, the rarity indicator representing a measure of how rare the name is in a population, and wherein determining a rarity indicator for the name further comprises the formula;
P(nameUniqueness)=1/((H*P(name))+1)wherein H denotes the size of the human population likely to be referenced in the document, P(name) is the name match probability score, and P(nameUniqueness) is the probability of name uniqueness; and
defining a hyperlink for the name based on the rarity indicator.
6 Assignments
0 Petitions
Accused Products
Abstract
Hyperlinking or associating documents to other documents based on the names of people in the documents has become more desirable. Although there is an automated system for installing such hyperlinks into judicial opinions, the system is not generally applicable to other types of names and documents, nor well suited to determine hyperlinks for names that might refer to two or more similarly named persons. Accordingly, the inventor devised systems, methods, and software that facilitate hyperlinking names in documents, regardless of type. One exemplary system includes a descriptor module and a linking module. The descriptor module develops descriptive patterns for selecting co-occurent document information that is useful in recognizing associations between names and professional classes. The linking module tags names in an input document, extracts co-occurent information using the descriptive patterns, and uses a Bayesian inference network that processes a (non-inverse-document-frequency) name-rarity score for each name along with the name and selected co-occurent document information to determine appropriate hyperlinks to other documents, such as entries in professional directories.
-
Citations
29 Claims
-
1. A computer-implemented method comprising:
-
identifying a name in a document; determining a rarity indicator for the name, the rarity indicator representing a measure of how rare the name is in a population, and wherein determining a rarity indicator for the name further comprises the formula;
P(nameUniqueness)=1/((H*P(name))+1)wherein H denotes the size of the human population likely to be referenced in the document, P(name) is the name match probability score, and P(nameUniqueness) is the probability of name uniqueness; and defining a hyperlink for the name based on the rarity indicator. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
-
-
12. A system for adding a hyperlink to a document including a person name, the system comprising:
-
at least one processor; a memory coupled to the processor, the memory including instructions for; identifying a name in a document; determining a rarity indicator for the name, the rarity indicator representing a measure of how likely the name is to refer to more than one entity in a population, and wherein determining a rarity indicator for the name further comprises the formula;
P(nameUniqueness)=1/((H*P(name))+1)wherein H denotes the size of the human population likely to be referenced in the document, P(name) is the name match probability score, and P(nameUniqueness) is the probability of name uniqueness; and defining a hyperlink for the name based on the rarity indicator. - View Dependent Claims (13, 14, 15, 16)
-
-
17. In a database of electronic records, a set of biographical records, each biographical record comprising:
-
a name representing a person associated with a biographical record; and a name-rarity indicator representing a measure of how likely the name is to refer to more than one entity in a population, wherein the name-rarity indicator is determined using the formula;
P(nameUniqueness)=1/((H*P(name))+1)wherein H denotes the size of the human population likely to be referenced in the document, P(name) is the name match probability score, and P(nameUniqueness) is the probability of name uniqueness. - View Dependent Claims (18, 19)
-
-
20. A computer-implemented method comprising:
-
receiving a search query including a name of an entity; determining a measure of how rare the name is in a population, and wherein determining a measure of how rare the name is in a population further comprises the formula;
P(nameUniqueness)=1/((H*P(name))+1)wherein H denotes the size of the human population likely to be referenced in the document, P(name) is the name match probability score, and P(nameUniqueness) is the probability of name uniqueness; and obtaining additional information to assist in answering the query, in response to the determined measure. - View Dependent Claims (21, 22, 23, 24, 25)
-
-
26. A computer-implemented method comprising:
-
identifying a name included within a set of text; determining rarity measure representing a likelihood of the identified name occurring in a population based at least in part on co-occurrence of a non-person-name term located in a document proximal to the name, and wherein determining rarity of a name in a population further comprises the formula;
P(nameUniqueness)=1/((H*P(name))+1)wherein H denotes the size of the human population likely to be referenced in the document, P(name) is the name match probability score, and P(nameUniqueness) is the probability of name uniqueness; and associating the identified name with a record in a database based at least in part on the rarity measure. - View Dependent Claims (27, 28, 29)
-
Specification