Approach to Recommending Mashups

Patent metadata

Field	Value
Publication number	US-2017277756-A1
Application number	US-201615077451-A
Country	US
Kind code	A1
Filing date	Mar 22, 2016
Priority date	Mar 22, 2016
Publication date	Sep 28, 2017
Grant date	—

Abstract

A method of recommending Mashups, including identifying, using a processor, pre-existing Mashups implementing application program interfaces (APIs), where each implemented API has one or more attached Tag(s) including API characteristics; extracting the characteristics from the Tags attached to the API(s) implemented in the Mashup, form a set including all of the characteristics from the APIs implemented in Mashup; identifying one or more API(s) not implemented in the Mashups; extracting the characteristics from the Tags attached to the API(s) not implemented in the Mashup to form another set; identifying API characteristics that are an element of one set, but not an element of the other set, forming a third set of these characteristics; modeling a relationship between API(s) using the sets; calculating the probability of one or more API(s) not implemented in a Mashup being used for new Mashup; and presenting the API(s) to a user for new Mashups.

First claim

What is claimed is:

1 . A method of recommending Mashups, comprising:
identifying, using a processor, one or more pre-existing Mashups, m j , implementing one or more application program interfaces (APIs), a i , where each implemented API has one or more attached Tag(s), T k , including one or more API characteristics, I; extracting the characteristics, I m , from the Tags, T k , attached to each of the API(s), ai, implemented in the Mashup, m j , to form a set, S m , including all of the extracted characteristics, I m , from all of the APIs, a i , implemented in Mashup, m j ; identifying one or more API(s), a x , not implemented in the existing Mashups; extracting the characteristics, I x , from the Tags attached to each of the API(s), a x , not implemented in the Mashup to form a set, S x , including all of the extracted characteristics, I x ; identifying one or more API characteristics, I q , that is an element of the set, S m , but not an element of set, S x ; forming a set, S q , including the one or more characteristics, I q ; modeling, using the processor, a relationship between API(s), a x , having characteristics, I x , and API(s), ai, having characteristics, I m , using the set, S m , and the set, S x ; calculating the probability of one or more API(s), a x , not implemented in a Mashup, m j , being used for a new Mashup; and presenting the one or more API(s), a x , to a user for use in the new Mashup.

2 . The method of claim 1 , which further comprises communicating via the processor, with one or more remote computer systems over a network to identify the one or more pre-existing Mashups, m j , and obtaining the characteristics, I m , stored as the one or more Tag(s), T k , attached to each implemented API, a i .

3 . The method of claim 2 , wherein the one or more remote computer systems is a server and the one or more pre-existing Mashups, m j , are stored in the one or more servers.

4 . The method of claim 1 , which further comprises selecting the one or more API(s), a x , to be presented to a user based on a maximum value of confidence, C.

5 . The method of claim 4 , which further comprises creating a new Mashup from the one or more API(s), a x , by preparing computer code, using the processor, that integrates functions and formats of the one or more API(s), a x .

6 . The method of claim 1 , wherein the modeling of the relationship between the API(s), a x , and API(s), includes determining an association rule from the set, S m , and the set, S x , that connect API(s), a x , with Mashups, m j .

7 . The method of claim 6 , wherein determining the association rule further comprises forming a Mashup-Tag pair to calculate the maximum value of the confidence for a specific pair of a Mashup and API.

8 . The method of claim 6 , wherein determining the association rule does not require a lower limit of confidence value.

9 . A mashup recommendation system, comprising:
a processor and memory; a mashup analyzer configured to identify, using the processor, one or more pre-existing Mashups, m j , implementing one or more application program interfaces (APIs), where each implemented API has one or more attached Tag(s), T k , including one or more API characteristics, I, and extract the characteristics, I m , from the Tags, T k , attached to each of the API(s), a i , implemented in the Mashup, m j , to form a set, S m , including all of the extracted characteristics, I m , from all of the APIs, a i , implemented in Mashup, m j ; identify one or more API(s), a x , not implemented in the existing Mashups; extracting the characteristics, I x , from the Tags attached to each of the API(s), a x , not implemented in the Mashup to form a set, S x , including all of the extracted characteristics, I x ; identifying one or more API characteristics, I q , that is an element of the set, S m , but not an element of set, S x ; forming a set, S q , including the one or more characteristics, I q ; an association rule modeler configured to model, using the processor, a relationship between API(s), a x , having characteristics, I x , and API(s), a i , having characteristics, I m , using the set, S m , and the set, S x ; and an API proposer configured to calculate the probability of one or more API(s), a x , not implemented in a Mashup, m j , being used for a new Mashup; and presenting the one or more API(s), a x , to a user for use in the new Mashup.

10 . The system of claim 9 , which further comprises a network interface configured to communicate via the processor, with one or more remote computer systems over a network to identify the one or more pre-existing Mashups, m j , and obtaining the characteristics, I m , stored as the one or more Tag(s), T k , attached to each implemented API, a i .

11 . The system of claim 10 , wherein the one or more remote computer systems is a server and the one or more pre-existing Mashups, m j , are stored in the one or more servers.

12 . The system of claim 9 , wherein the API proposer is configured to select the one or more API(s), a x , to be presented to a user based on a maximum value of confidence, C.

13 . The method of claim 12 , wherein the API proposer is configured to create a new Mashup, using the processor, from the one or more API(s), a x , by preparing computer code, using the processor, that integrates functions and formats of the one or more API(s), a x .

14 . The method of claim 9 , wherein the modeling of the relationship between the API(s), a x , and API(s), a i , includes determining an association rule that connect API(s), a x , with Mashups, m j from the set, S m , and the set, S x .

15 . The method of claim 14 , wherein determining the association rule further comprises forming a Mashup-Tag pair to calculate the maximum value of the confidence for a specific pair of a Mashup and API.

16 . The method of claim 14 , wherein determining the association rule does not require requires a lower limit of confidence value.

17 . A non-transitory computer readable storage medium comprising a computer readable program for a method of recommending Mashups, wherein the computer readable program when executed on a computer causes the computer to perform the steps of:
identifying, using a processor, one or more pre-existing Mashups, m j , implementing one or more application program interfaces (APIs), a i , where each implemented API has one or more attached Tag(s), T k , including one or more API characteristics, I; extracting the characteristics, I m , from the Tags, T k , attached to each of the API(s), implemented in the Mashup, m j , to form a set, S m , including all of the extracted characteristics, I m , from all of the APIs, a i , implemented in Mashup, m j ; identifying one or more API(s), a x , not implemented in the existing Mashups; extracting the characteristics, I x , from the Tags attached to each of the API(s), a x , not implemented in the Mashup to form a set, S x , including all of the extracted characteristics, I x ; identifying one or more API characteristics, I q , that is an element of the set, S m , but not an element of set, S x ; forming a set, S q , including the one or more characteristics, I q ; modeling, using the processor, a relationship between API(s), a x , having characteristics, I x , and API(s), having characteristics, I m , using the set, S m , and the set, S x ; calculating the probability of one or more API(s), a x , not implemented in a Mashup, m j , being used for a new Mashup; and presenting the one or more API(s), a x , to a user for use in the new Mashup

Assignees

• IBM

Inventors

• Masuda Satoshi
• Suzuki Akiko
• Nakamura Hiroaki
• Takase Toshiro

Classifications

• G06F9/5072 Primary

  Grid computing · CPC title

• G06F17/30554

  Physics · mapped topic

• G06F17/3056

  Physics · mapped topic

• G06F17/30598

  Physics · mapped topic

• G06F17/30525 Primary

  Physics · mapped topic