Automated system and method for generating reasons that a court case is cited
A computer-automated system and method identify text in a first “citing” court case, near a “citing instance” (in which a second “cited” court case is cited), that indicates the reason(s) for citing (RFC). The automated method of designating text, taken from a set of citing documents, as reasons for citing (RFC) that are associated with respective citing instances of a cited document, has steps including: obtaining contexts of the citing instances in the respective citing documents (each context including text that includes the citing instance and text that is near the citing instance), analyzing the content of the contexts, and selecting (from the citing instances' context) text that constitutes the RFC, based on the analyzed content of the contexts. A related computer-automated system and method selects content words that are highly related to the reasons a particular document is cited, and gives them weights that indicate their relative relevance. Another related computer-automated system and method forms lists of morphological forms of words. Still another related computer-automated system and method scores sentences to show their relevance to the reasons a document is cited. Also, another related computer-automated system and method generates lists of content words. In a preferred embodiment, the systems and methods are applied to legal (especially case law) documents and legal (especially case law) citations.
1. An automated method of scoring sentences in citing documents, to indicate relevance of content of the respective sentences to reasons that a cited document is cited, the method comprising:
calculating respective initial content scores (ICSs) for the sentences in the citing documents, based on the content of the sentences;
calculating respective distances (Ds) of the sentences in the citing documents from respective citing instances of the cited document; and
calculating respective content scores (CSs) for the sentences in the citing documents, based on at least the ICSs and the distances.
2. The method of claim 1 , further comprising normalizing the ICSs to form normalized initial content scores (NICSs) for use by the CS calculation step, by taking into account:
a) numbers of words in the respective sentences; and
b) a largest frequency count in a content word list that includes:
1) a set of content words that are found in the sentences of the citing documents, and
2) a set of frequency counts linked to corresponding content words in the set of content words.
3. The method of claim 1 , further comprising:
modifying the distances D to norm respective modified absolute distances (MADs) for use by the CS calculation step, based on criteria relating to predetermined statistical observations of the implications of placement of a sentence in the citing document relative to the citing instance.
4. The method of claim 3 , wherein the criteria include: whether the sentence is in the same paragraph as the citing instance.
5. The method of claim 3 , wherein the criteria include: whether the sentence is located after the citing instance.
6. An apparatus of scoring sentences in citing documents, to indicate relevance of content of the respective sentences to reasons that a cited document is cited, the apparatus comprising:
means for calculating respective initial content scores (ICSs) for the sentences in the citing documents, based on the content of the sentences;
means for calculating respective distances (Ds) of the sentences in the citing documents from respective citing instances of the cited document; and
means for calculating respective content scores (CSs) for the sentences in the citing documents, based on at least the ICSs and the distances.
7. The apparatus of claim 6 , further comprising means for normalizing the ICSs to form normalized initial content scores (NICSs) for use by the CS calculation means, by taking into account:
a) numbers of words in the respective sentences, and
b) a largest frequency count in a content word list that includes:
1) a set of content words that are found in the sentences of the citing documents, and
2) a set of frequency counts linked to corresponding content words in the set of content words.
8. The apparatus of claim 6 , further comprising:
means for modifying the distances D to form respective modified absolute distances (MADs) for use by the CS calculation means, based on criteria relating to predetermined statistical observations of the implications of placement of a sentence in the citing document relative to the citing instance.
9. The apparatus of claim 8 , wherein the criteria include: whether the sentence is in the same paragraph as the citing instance.
10. The apparatus of claim 8 , wherein the criteria include: whether the sentence is located after the citing instance.
11. A computer-readable memory that, when used in conjunction with a computer, can carry out an automated method of scoring sentences in citing documents, to indicate relevance of content of the respective sentences to reasons that a cited document is cited, the computer-readable memory comprising:
computer-readable code for calculating respective initial content scores (ICSs) for the sentences in the citing documents, based on the content of the sentences;
computer-readable code for calculating respective distances (Ds) of the sentences in the citing documents from respective citing instances of the cited document; and
computer-readable code for calculating respective content scores (CSs) for the sentences in the citing documents, based on at least the ICSs and the distances.
12. The computer-readable memory of claim 11 , further comprising computer-readable code for normalizing the ICSs to form normalized initial content scores (NICSs) for use by the CS calculation computer-readable code, by taking into account:
a) numbers of words in the respective sentences, and
b) a largest frequency count in a content word list that includes:
1) a set of content words that are found in the sentences of the citing documents, and
2) a set of frequency counts linked to corresponding content words in the set of content words.
13. The computer-readable memory of claim 11 , further comprising:
computer-readable code for modifying the distances D to form respective modified absolute distances (MADs) for use by the CS calculation computer-readable code, based on criteria relating to predetermined statistical observations of the implications of placement of a sentence in the citing document relative to the citing instance.
14. The computer-readable memory of claim 13 , wherein the criteria include:
whether the sentence is in the same paragraph as the citing instance.
15. The computer-readable memory of claim 13 , wherein the criteria include:
whether the sentence is located after the citing instance.