Systems and methods for visual definition of data associations
Systems and methods are disclosed for visual definitions of data associations. In accordance with one implementation, a method is provided for visual definitions of data associations. The method includes obtaining and displaying a first sample document, receiving a first input indicating selection of one or more objects within the first sample document, and determining a first set of one or more characteristics shared by the selected objects. The method also includes identifying, within one or more target documents, one or more target objects characterized by the first set of one or more characteristics, and storing object data associated with the target objects.
1. An electronic device comprising:
one or more computer-readable storage media configured to store instructions; and
one or more processors configured to execute the instructions to cause the electronic device to:
obtain and display a first sample document;
receive a first input indicating selection of one or more objects within the first sample document;
determine a first set of one or more characteristics shared by the selected objects;
assign weights to one or more characteristics of the first set of one or more characteristics;
identify one or more target objects characterized by the first set of one or more characteristics that include the one or more assigned weights, wherein the one or more target objects include one or more characteristics with a single or combined weight above a threshold; and
store object data associated with the target objects.
2. The electronic device of claim 1 , wherein the identification of the one or more target objects is in response to the one or more target objects having one or more characteristics with a single or combined weight above a threshold.
3. The electronic device of claim 1 , wherein the one or more processors are further configured to execute the instructions to cause the electronic device to obtain one or more target documents based on previously identified target objects.
4. The electronic device of claim 1 , wherein the one or more processors are further configured to execute the instructions to cause the electronic device to:
receive a second input indicating de-selection of one or more previously selected objects; and
determine a second set of characteristics based on the first and second inputs.
5. The electronic device of claim 1 , wherein the selected objects further includes objects automatically selected by the electronic device, wherein the objects automatically selected by the electronic device are also characterized by the first set of one or more characteristics.
6. The electronic device of claim 1 , wherein the one or more processors are further configured to execute the instructions to cause the electronic device to:
highlight at least one of the identified one or more target objects in at least a document of one or more target documents.
7. The electronic device of claim 1 , wherein at least a portion of the selected objects are references, and wherein the one or more processors are further configured to execute the instructions to cause the electronic device to:
determine a set of objects associated with the references;
determine a second set of one or more characteristics shared by the set of objects;
identify one or more secondary target objects characterized by the second set of one or more characteristics; and
store object data associated with the secondary target objects.
8. The electronic device of claim 1 , wherein the one or more processors are further configured to execute the instructions to cause the electronic device to:
determine if a characteristic of an object is a link to a second document; and
if the characteristic of the object is a link to the second document, identify target objects in the second document.
9. A method performed by at least one electronic device comprising one or more processors, the method comprising:
obtaining and displaying a first sample document;
receiving a first input indicating selection of one or more objects within the first sample document;
determining a first set of one or more characteristics shared by the selected objects;
assigning weights to one or more characteristics of the first set of one or more characteristics;
identifying one or more target objects characterized by the first set of one or more characteristics that include the one or more assigned weights, wherein the one or more target objects include one or more characteristics with a single or combined weight above a threshold; and
storing object data associated with the target objects.
10. The method of claim 9 , wherein the identification of the one or more target objects is in response to the one or more target objects having one or more characteristics with a single or combined weight above a threshold.
11. The method of claim 9 , further comprising obtaining one or more target documents based on previously identified target objects.
12. The method of claim 9 , further comprising:
receiving a second input indicating de-selection of one or more previously selected objects; and
determining a second set of characteristics based on the first and second inputs.
13. The method of claim 9 , wherein the selected objects further includes objects automatically selected by the electronic device, wherein the objects automatically selected by the electronic device are also characterized by the first set of one or more characteristics.
14. The method of claim 9 , further comprising highlighting at least one of the identified one or more target objects in at least a document of one or more target documents.
15. The method of claim 9 , wherein at least a portion of the selected objects are references, and further comprising:
determining a set of objects associated with the references;
determining a second set of one or more characteristics shared by the set of objects;
identifying one or more secondary target objects characterized by the second set of one or more characteristics; and
storing object data associated with the secondary target objects.
16. The method of claim 9 , further comprising:
determining if a characteristic of an object is a link to a second document; and
if the characteristic of the object is a link to the second document, identifying target objects in the second document.
17. A non-transitory computer-readable medium storing a set of instructions that are executable by one or more electronic devices, each having one or more processors, to cause the one or more electronic devices to perform a method, the method comprising:
obtaining and displaying a first sample document;
receiving a first input indicating selection of one or more objects within the first sample document;
determining a first set of one or more characteristics shared by the selected objects;
assigning weights to one or more characteristics of the first set of one or more characteristics;
identifying one or more target objects characterized by the first set of one or more characteristics that include the one or more assigned weights, wherein the one or more target objects include one or more characteristics with a single or combined weight above a threshold; and
storing object data associated with the target objects.
18. The non-transitory computer-readable medium of claim 17 , wherein the identification of the one or more target objects is in response to the one or more target objects having one or more characteristics with a single or combined weight above a threshold.