RankSys - Revision history

Saulvargas at 11:43, 14 February 2016

2016-02-14T11:43:08Z

Saulvargas at 16:32, 13 October 2015

2015-10-13T16:32:29Z

Alan at 11:15, 31 July 2015

2015-07-31T11:15:24Z

Saulvargas at 22:07, 18 May 2015

2015-05-18T22:07:03Z

Saulvargas at 20:23, 18 May 2015

2015-05-18T20:23:15Z

Saulvargas at 13:51, 27 March 2015

2015-03-27T13:51:12Z

Saulvargas at 13:50, 27 March 2015

2015-03-27T13:50:39Z

Saulvargas: Created page with "RankSys is a new framework for the implementation and evaluation of recommendation algorithms and techniques that has resulted from a line of research work that is currently d..."

2015-03-24T15:23:08Z

Created page with "RankSys is a new framework for the implementation and evaluation of recommendation algorithms and techniques that has resulted from a line of research work that is currently d..."

New page

RankSys is a new framework for the implementation and evaluation of recommendation algorithms and techniques that has resulted from a line of research work that is currently documented in several publications and a PhD thesis (see [http://ir-uam.github.io/RankSys/ RankSys webpage]). While it is envisioned as a framework for the generic experimentation of recommendation technologies, it includes substantial support focusing on the evaluation and enhancement of novelty and diversity. RankSys derives its name from explicitly targeting the ranking task problem, rather than rating prediction. This decision is reflected in the design of the different core interfaces and components of the framework.

The framework has been programmed with Java 8. We take advantage of many of the new features of the language, such as the use of lambda functions, Stream's and facilities for automatic parallelization of the code. The code licensed under the GPL V3, which allows the free use, study, distribution and modification of the software as long as derived works are distributed under the same license.

To date, the publicly available version of this framework includes the modules that implement novelty and diversity metrics and re-ranking techniques and the required core components of the framework:

* RankSys-core, which contains the common and auxiliary classes of the framework.
* RankSys-metrics, which contains the interfaces and common components for defining metrics.
* RankSys-diversity, which contains the novelty and diversity metrics and re-ranking strategies.
* RankSys-examples, which provides examples of usage of the previous modules.

If you want to know more, the [http://ir-uam.github.io/RankSys/ webpage of the project] provides a high-level description of the different components of the current release of the software and [https://github.com/ir-uam/RankSys GitHub] hosts the source code.

== External links ==
* Webpage: http://ir-uam.github.io/RankSys/
* GitHub repository: https://github.com/ir-uam/RankSys

[[Category: Java]]
[[Category: Software]]

@@ Line 1: / Line 1: @@
-'''RankSys''' is a new [[framework]] for the implementation and [[evaluation]] of [[recommendation algorithms]] and techniques that has resulted from a line of research work that is currently documented in several publications and a PhD thesis (see [http://ranksys.github.io/ RankSys webpage]). While it is envisioned as a framework for the generic experimentation of recommendation technologies, it includes substantial support focusing on the evaluation and enhancement of [[novelty]] and [[diversity]]. RankSys derives its name from explicitly targeting the [[ranking]] task problem, rather than [[rating prediction]]. This decision is reflected in the design of the different core interfaces and components of the framework.
+'''RankSys''' is a new [[framework]] for the implementation and [[evaluation]] of [[recommendation algorithms]] and techniques that has resulted from a line of research work that is currently documented in several [https://github.com/RankSys/RankSys/wiki/References publications] and a [http://saulvargas.es/phd-thesis.pdf PhD thesis]. While it is envisioned as a framework for the generic experimentation of recommendation technologies, it includes substantial support focusing on the evaluation and enhancement of [[novelty]] and [[diversity]]. RankSys derives its name from explicitly targeting the [[ranking]] task problem, rather than [[rating prediction]]. This decision is reflected in the design of the different core interfaces and components of the framework.
-The framework has been programmed with Java 8. We take advantage of many of the new features of the language, such as the use of lambda functions, Stream's and facilities for automatic parallelization of the code. The code licensed under the GPL V3, which allows the free use, study, distribution and modification of the software as long as derived works are distributed under the same license.
+The framework has been programmed with Java 8, which is the most recent version of the popular programming language. We take advantage of many of the new features of the language, such as the use of lambda functions, Stream's and facilities for automatic parallelization of the code. The code licensed under the [https://www.mozilla.org/en-US/MPL/2.0/ MPL 2.0].
-The publicly available version of this framework (v0.3) includes implementations of several collaborative filtering recommendation algorithms as well as a wide variety of novelty and diversity metrics and re-ranking techniques. The modules published to date are the following:
+The publicly available version of this framework (0.4.2) includes implementations of several collaborative filtering recommendation algorithms, a wide variety of novelty and diversity metrics and re-ranking techniques and state-of-the-art compression techniques for in-memory collaborative filtering data. If you want to know more, check the [https://github.com/RankSys/RankSys GitHub site] or the [https://github.com/RankSys/RankSys/wiki wiki], which provides a high-level description of the different components of the current release of the software. Finally, [https://twitter.com/RankSys follow us in Twitter] to keep in touch!
 == External links ==
-* Webpage: http://ranksys.github.io/
+* Webpage: http://ranksys.org/
 * GitHub repository: https://github.com/RankSys/RankSys
 * Wiki: http://github.com/RankSys/RankSys/wiki
 [[Category: Java]]
 [[Category: Software]]

@@ Line 1: / Line 1: @@
-'''RankSys''' is a new [[framework]] for the implementation and [[evaluation]] of [[recommendation algorithms]] and techniques that has resulted from a line of research work that is currently documented in several publications and a PhD thesis (see [http://ir-uam.github.io/RankSys/ RankSys webpage]). While it is envisioned as a framework for the generic experimentation of recommendation technologies, it includes substantial support focusing on the evaluation and enhancement of [[novelty]] and [[diversity]]. RankSys derives its name from explicitly targeting the [[ranking]] task problem, rather than [[rating prediction]]. This decision is reflected in the design of the different core interfaces and components of the framework.
+'''RankSys''' is a new [[framework]] for the implementation and [[evaluation]] of [[recommendation algorithms]] and techniques that has resulted from a line of research work that is currently documented in several publications and a PhD thesis (see [http://ranksys.github.io/ RankSys webpage]). While it is envisioned as a framework for the generic experimentation of recommendation technologies, it includes substantial support focusing on the evaluation and enhancement of [[novelty]] and [[diversity]]. RankSys derives its name from explicitly targeting the [[ranking]] task problem, rather than [[rating prediction]]. This decision is reflected in the design of the different core interfaces and components of the framework.
 The framework has been programmed with Java 8. We take advantage of many of the new features of the language, such as the use of lambda functions, Stream's and facilities for automatic parallelization of the code. The code licensed under the GPL V3, which allows the free use, study, distribution and modification of the software as long as derived works are distributed under the same license.
@@ Line 16: / Line 16: @@
 * RankSys-examples, which provides examples of usage of the previous modules.
-If you want to know more, the [http://github.com/ir-uam/RankSys/wiki wiki of the project] provides a high-level description of the different components of the current release of the software and [https://github.com/ir-uam/RankSys GitHub] hosts the source code.
+If you want to know more, the [http://github.com/RankSys/RankSys/wiki wiki of the project] provides a high-level description of the different components of the current release of the software and [https://github.com/RankSys/RankSys GitHub] hosts the source code.
 == External links ==
-* Webpage: http://ir-uam.github.io/RankSys/
+* Webpage: http://ranksys.github.io/
-* GitHub repository: https://github.com/ir-uam/RankSys
+* GitHub repository: https://github.com/RankSys/RankSys
-* Wiki: http://github.com/ir-uam/RankSys/wiki
+* Wiki: http://github.com/RankSys/RankSys/wiki
 [[Category: Java]]
 [[Category: Software]]

← Older revision		Revision as of 11:15, 31 July 2015
Line 1:		Line 1:
−	RankSys is a new framework for the implementation and evaluation of recommendation algorithms and techniques that has resulted from a line of research work that is currently documented in several publications and a PhD thesis (see [http://ir-uam.github.io/RankSys/ RankSys webpage]). While it is envisioned as a framework for the generic experimentation of recommendation technologies, it includes substantial support focusing on the evaluation and enhancement of novelty and diversity. RankSys derives its name from explicitly targeting the ranking task problem, rather than rating prediction. This decision is reflected in the design of the different core interfaces and components of the framework.	+	'''RankSys''' is a new [[framework]] for the implementation and [[evaluation]] of [[recommendation algorithms]] and techniques that has resulted from a line of research work that is currently documented in several publications and a PhD thesis (see [http://ir-uam.github.io/RankSys/ RankSys webpage]). While it is envisioned as a framework for the generic experimentation of recommendation technologies, it includes substantial support focusing on the evaluation and enhancement of [[novelty]] and [[diversity]]. RankSys derives its name from explicitly targeting the [[ranking]] task problem, rather than [[rating prediction]]. This decision is reflected in the design of the different core interfaces and components of the framework.

	The framework has been programmed with Java 8. We take advantage of many of the new features of the language, such as the use of lambda functions, Stream's and facilities for automatic parallelization of the code. The code licensed under the GPL V3, which allows the free use, study, distribution and modification of the software as long as derived works are distributed under the same license.		The framework has been programmed with Java 8. We take advantage of many of the new features of the language, such as the use of lambda functions, Stream's and facilities for automatic parallelization of the code. The code licensed under the GPL V3, which allows the free use, study, distribution and modification of the software as long as derived works are distributed under the same license.

@@ Line 3: / Line 3: @@
 The framework has been programmed with Java 8. We take advantage of many of the new features of the language, such as the use of lambda functions, Stream's and facilities for automatic parallelization of the code. The code licensed under the GPL V3, which allows the free use, study, distribution and modification of the software as long as derived works are distributed under the same license.
-The publicly available version of this framework (v0.3) includes implementations of several collaborative filtering recommendation algorithms as well as wide variety of novelty and diversity metrics and re-ranking techniques. The modules published to date are the following:
+The publicly available version of this framework (v0.3) includes implementations of several collaborative filtering recommendation algorithms as well as a wide variety of novelty and diversity metrics and re-ranking techniques. The modules published to date are the following:
 * RankSys-core, which contains the common and auxiliary classes of the framework.

@@ Line 10: / Line 10: @@
 * RankSys-examples, which provides examples of usage of the previous modules.
-If you want to know more, the [http://ir-uam.github.io/RankSys/ wiki of the project] provides a high-level description of the different components of the current release of the software and [https://github.com/ir-uam/RankSys GitHub] hosts the source code.
+If you want to know more, the [http://github.com/ir-uam/RankSys/wiki wiki of the project] provides a high-level description of the different components of the current release of the software and [https://github.com/ir-uam/RankSys GitHub] hosts the source code.
 == External links ==