RecSysWiki - User contributions [en]

User:IgorBrigadir

2022-01-31T22:37:18Z

IgorBrigadir:

Senior Research Engineer at recsyslabs in the Insight Centre for Data Analytics, based in UCD, Ireland. DM me on Twitter[https://twitter.com/IgorBrigadir] if you need a new account on this wiki.

User:IgorBrigadir

2021-12-01T04:07:11Z

IgorBrigadir:

Senior Research Engineer at recsyslabs in the Insight Centre for Data Analytics, based in UCD, Ireland. DM me on Twitter[https://twitter.com/IgorBrigadir].

User:IgorBrigadir

2021-12-01T04:06:51Z

IgorBrigadir:

Senior Research Engineer at recsyslabs in the Insight Centre for Data Analytics, based in UCD, Ireland. DM me on Twitter[[https://twitter.com/IgorBrigadir]].

User:IgorBrigadir

2021-12-01T04:06:01Z

IgorBrigadir:

Senior Research Engineer at recsyslabs in the Insight Centre for Data Analytics, based in UCD, Ireland. DM me on [[https://twitter.com/IgorBrigadir|Twitter]].

Main Page

2021-12-01T04:04:25Z

IgorBrigadir: add registration note

{{DISPLAYTITLE:<span style="display:none">{{FULLPAGENAME}}</span>}}
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<div style="font-size:162%;border:none;margin: 0;padding:.1em;color:#000">Welcome to the Recommender Systems Wiki (RecSysWiki) </div>
<div style="top:+0.2em;font-size: 95%">''sharing information on all aspects of [[Recommender System|Recommender Systems]]''</div>
<div id="articlecount" style="width:100%;text-align:center;font-size:85%;">'''{{NUMBEROFPAGES}}''' pages and '''{{NUMBEROFARTICLES}}''' articles, created by [[Special:ActiveUsers|{{NUMBEROFUSERS}} users]] as of {{CURRENTDAYNAME}}, {{CURRENTMONTHNAME}} {{CURRENTDAY}}, {{CURRENTYEAR}}</div>
<div style="width:100%;text-align:center;font-size:85%;">started on February 10th, 2011</div>
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[[RecSysWiki:About|This Wiki]] is about everything related to [[Recommender System|Recommender Systems]].

[[Special:CreateAccount|Registration]] is open to anyone who wishes to contribute, but please contact an [[User:IgorBrigadir|administrator]] to get a new account.


{|style="border-spacing:8px;margin:0px -8px"
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{|width="100%" cellpadding="2" cellspacing="5" style="vertical-align:top;background-color:#f5fffa"
! <h2 style="margin:0;background-color:#cef2e0;font-size:120%;font-weight:bold;border:1px solid #a3bfb1;text-align:left;color:#000;padding:0.2em 0.4em;">Categories in RecSysWiki</h2>
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* [[:Category:API|APIs]]
* [[:Category:Book|Books]]
* [[:Category:Class|Classes]]
* [[:Category:Company|Companies]]
* [[:Category:Competition|Competitions]]
* [[:Category:Conference|Conferences]]
* [[:Category:Dataset|Datasets]]
* [[:Category:Educational recommender systems|Educational Recommender Systems]]
* [[:Category:Evaluation|Evaluation]]
* [[:Category:Evaluation measure|Evaluation Measures]]
* [[:Category:Event|Events]]
* [[:Category:Fashion recommendation|Fashion Recommendation]]
* [[:Category:Job offer|Job Offers]]
* [[:Category:Journal|Journals]]
* [[:Category:List|Lists]]
* [[:Category:Literature|Literature]]
* [[:Category:Method|Methods]]
* [[:Category:Movie recommendation|Movie Recommendation]]
* [[:Category:Music recommendation|Music Recommendation]]
* [[:Category:Paper|Papers]]
* [[:Category:People|People]]
* [[:Category:Project|Projects]]
* [[:Category:Research group|Research Groups]]
* [[:Category:Software|Software]]
* [[:Category:Task|Task]]
* [[:Category:User-centric evaluation|User-centric evaluation]]
* [[:Category:Workshop|Workshops]]

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<h2 style="margin:0;background-color:#cedff2;font-size:120%;font-weight:bold;border:1px solid #a3b0bf;text-align:left;color:#000;padding:0.2em 0.4em;">Information on RecSysWiki</h2>
|-
|style="color:#000"|
* [[:RecSysWiki:Current events| Current Events]]
* [[Special:Statistics|RecSysWiki statistics]]
* [[Special:AllPages|All pages]]
* [[Special:Categories|All categories]]
* [[Special:WantedPages|Wanted pages]]
* [[To Do List]] - ''please help by contributing''

<h2 style="margin:0;background-color:#cedff2;font-size:120%;font-weight:bold;border:1px solid #a3b0bf;text-align:left;color:#000;padding:0.2em 0.4em;">Recent additions and updates</h2>
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* [[Open positions at Zalando 2020]] 
* [[Recommendation Datasets]] 
* [[Recommendation Software]] 
* [[List of recommender systems master's theses | Master's Theses]] 
* [[TagRec]] 
* [[CrowdRec]] 
* [[RecSysChallenge]] 
* [[LibRec]] 
* [[Test.fm]] 
* [[Okapi]] 
* [[ORP]] 
* [[RecSys-frontend]] 
* [[Dissertations]] 
* [[RiVal]] 
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[[Category:RecSys Wiki Information]]

RecSysWiki:Current events

2021-11-19T04:51:05Z

IgorBrigadir: Recsys 2021

''Feel free to add current/upcoming events about recommender systems here.''

__NOTOC__

== Ongoing ==

* 2021-09-27: [https://recsys.acm.org/recsys21/dates/ ACM RecSys 2021]

== Upcoming ==

[[Category: Event| ]]

Recommender Systems Challenge

2021-01-25T05:14:31Z

IgorBrigadir: fix links

The '''Recommender Systems Challenge''' is the official challenge of the [[ACM RecSys]] conference series. The challenge started with the [[CAMRa 2010]] challenge at [[RecSys 2010]]. Since 2012, the challenges at RecSys have been labeled RecSysChallenge.

===External links===
* [http://recsys.acm.org/honors-and-awards/challenges/ List of RecSys Challenge winners]
* [http://www.dai-labor.de/camra2010/ CAMRa2010] Context-Aware Movie Recommendation
* [https://web.archive.org/web/20160310010222/http://2011.camrachallenge.com/ CAMRa2011] Context-Aware Movie Recommendation
* [http://2012.recsyschallenge.com RecSysChallenge 2012] Two tracks: CAMRa (Context-Aware Movie Recommendation) and ScienceRec (Scientific Paper Recommendation)
* [http://2013.recsyschallenge.com RecSysChallenge 2013] Yelp Business Rating Prediction
* [http://2014.recsyschallenge.com RecSysChallenge 2014] User Engagement as Evaluation using [[MovieTweetings]]
* [http://2015.recsyschallenge.com RecSysChallenge 2015] YooChoose e-commerce click and buy prediction
* [http://2016.recsyschallenge.com RecSysChallenge 2016] XING job posting recommendation
* [http://2017.recsyschallenge.com RecSysChallenge 2017] XING job posting recommendation in a cold-start setting.
* [http://2018.recsyschallenge.com RecSysChallenge 2018] Spotify automatic playlist continuation
* [http://www.recsyschallenge.com/2019 RecSysChallenge 2019] Trivago session-based and context-aware accommodation recommendation
* [http://www.recsyschallenge.com/2020 RecSysChallenge 2020] Twitter engagement prediction

[[Category:event]]
[[Category:competition]]

Common Recommender REST API

2020-07-26T23:25:01Z

IgorBrigadir: Add link to OpenAPI spec on github

The [[MyMediaLite]] and [[LensKit]] projects are seeking to use a '''Common Recommender [[Wikipedia:REST|REST API]]''' for recommender web applications.
Specific implementations are encouraged to support the following core interface, but may extend the API as necessary.

The API is based upon three basic entities:
* Users (referenced by a unique "'''uid'''")
* Items (referenced by a unique "'''iid'''")
* Events (referenced by a unique "'''eid'''")

User, item, and event IDs are strings, but implementations will most likely specify a valid ID format.

An additional type of ID, a revision ID ("'''rid'''"), is used to identify any change to a user, item, or event. When one of these entities is either returned, created or updated, the server will return a revision ID in its response. When a client wishes to make changes to a user, item, or event, it must provide the ID of the entity's most recent revision. If this ID is not valid, the client's request will fail.

Each user and item is associated with a set of events. An event is created whenever a user takes some meaningful action involving an item, such as a rating or purchase. This event is then associated with both the user and the item. The specific event types that are supported will vary between different implementations.

==Working with Users==

====Add New User====
;<tt>POST /users</tt>
:Adds a new user to the server. If a user ID is specified in the request body, and currently unused, the user is assigned the ID. If an existing user possesses the ID, the request fails.
:The request body may also contain events related to this user.
:If no ID is specified, one is is generated for the user by the server and returned in the response.
:The request will also return a new revision ID for use by a future update request.

====Add New or Update Existing User====
;<tt>PUT /users/[uid]</tt>
:If the specified ID is unused, a new user is created and assigned this ID.
:If an existing user possesses the ID, the request must provide the user's most recent revision ID in order to update their data.
:The request will return a new revision ID for use by a future update request.

====Retrieve User Metadata====
;<tt>GET /users/[uid]</tt>
:Retrieves user data from the server. This includes user attributes, but does not include the user's history of events.

====Remove User from Server====
;<tt>DELETE /users/[uid]</tt>
:Deletes the specified user from the server. Precise behavior will vary between implementations.

====Access User Statistics====
;<tt>GET /users/[uid]/statistics</tt>
:Retrieves common statistics regarding the specified user. Implementations are free to specify their own fields.

====Retrieve User Rating Predictions====
=====Basic HTTP Calls=====
;<tt>GET /users/[uid]/predictions</tt>
:Retrieves user rating predictions for all possible items.

=====Query Parameters=====
;<var>item</var>
:The ID of an item for which a rating prediction is to be retrieved. Multiple IDs can be specified simultaneously. If no IDs are specified, the server will return predictions for all possible items.
:ex: <tt>GET /users/predictions?item=42&item=70</tt> Retrieves user rating predictions for items 42 and 70.

;<var>useStoredRatings</var>
:Enables the server to return a user rating rather than a prediction if one has been provided for an item.
:ex: <tt>GET /users/predictions?usedStoredRatings=true</tt> Allows the server to retrieve user ratings in place of predictions when they are available.

====Retrieve User Item Recommendations====
=====Basic HTTP Calls=====
;<tt>GET /users/[uid]/recommendations</tt>
:Retrieves the complete recommendation set for the specified user. If possible, items are returned in ranked order.

=====Query Parameters=====
;<var>count</var>
:The maximum number of recommendations to be returned. If this maximum cannot be reached, the server returns as many recommendations as possible.
:ex: <tt>GET /users/[uid]/recommendations?count=10</tt> Retrieves a maximum of 10 recommended items.

====Access User History====
The supported event types will vary between implementation. Each of these event types may also support a unique set of query parameters.
=====Basic HTTP Calls=====
;<tt>GET /users/[uid]/events</tt>
:Retrieves all events associated with the specified user.

;<tt>GET /users/[uid]/events/purchases</tt>
:Retrieve all events of a specific type (In this case, purchases) associated with the specified user.

;<tt>GET /users/[uid]/currentRatings</tt>
:Retrieves a simple vector containing the most recent rating of each item currently rated by the user.
:Note that this will return the same set of events as <tt>GET /users/[uid]/events/ratings?history=current&null=false</tt>, but in a simple vector form.

=====Query Parameters=====
;<var>item</var>
:<i>Required for all Event Types</i>
:The ID of an item with which all returned events are associated. If no ID is specified, the server will consider all possible items.
:ex: <tt>GET /users/[uid]/events/purchases?item=42&item=70</tt> Retrieves all user purchase events associated with items 42 and 70.

;<var>history</var>
:<i>Required for all Event Types</i>
:The time period during which all returned events occurred.
:ex: <tt>GET /users/[uid]/events?history=1m</tt> Retrieves all events associated with the user that have occurred within the past month.

;<var>null</var>
:<i>Required Specifically for the Rating Event Type</i>
:Instructs the server to exclude any null ratings from the returned collection of events. By default, null-valued ratings are included.
:ex: <tt>GET /users/[uid]/events/ratings?item=42&item=70&null=false</tt> Returns all user rating events associated with items 42 and 70, excluding any null ratings.

====Add New Event to User History====
;<tt>POST /users/[uid]/events/ratings</tt>
:Add a new event of the specified type (In this case, a rating) to the server. If an ID is specified in the request body, the event is given the specified ID.
:Otherwise, the server generates an ID for the event and returns it in the response.

==Working with Items==
====Add New Item to Server====
;<tt>POST /items</tt>
:Adds a new item to the server. If an item ID is specified and currently unused, the item is assigned this ID. If an existing item possesses the ID, the request fails.
:If no ID is specified, one is is generated for the item by the server and returned in the response.
:The request will also return a new revision ID for use by a future update request.

====Add New or Update Existing Item====
;<tt>PUT /items/[iid]</tt>
:If the specified ID is unused, a new item is created and assigned the ID.
:If an existing item possesses the ID, the request must provide the item's most recent revision ID in order to update its data.
:The request will return a new revision ID for use by a future update request.

====Retrieve Item Metadata====
;<tt>GET /items/[iid]</tt>
:Retrieves item data from the server. This includes item attributes, but does not include the item's history of events.

====Remove Item from Server====
;<tt>DELETE /items/[iid]</tt>
:Deletes the item with the specified ID from the server. Precise behavior will vary between implementations.

====Access Item Statistics====
;<tt>GET /items/[iid]/statistics</tt>
:Retrieves common statistics regarding the specified item. Implementations are free to define their own fields.

====Access Item History====
Supported event types and query parameters will vary between implementations.
=====Basic HTTP Calls=====
;<tt>GET /items/[iid]/events</tt>
:Retrieves all events associated with the specified item.

;<tt>GET /items/[iid]/events/ratings</tt>
:Retrieve all events of a specific type (In this case, ratings) associated with the specified item.

=====Query Parameters=====
;<var>user</var>
:<i>Required for all Event Types</i>
:The ID of a user with which all returned events are associated. If no user ID is specified, the server will consider all possible users.
:ex: <tt>GET /items/[iid]/events/ratings?user=18&user=41</tt> Retrieves all item rating events associated with users 18 and 41.

;<var>history</var>
:<i>Required for all Event Types</i>
:The time period during which all returned events occurred
:ex: <tt>GET /items/[iid]/events?history=1m</tt> Retrieves all events associated with the item that have occurred within the past month.

;<var>null</var>
:<i>Required for the Rating Event Type</i>
:Instructs the server to exclude null ratings. By default, null-valued ratings are included.
:ex: <tt>GET /items/[iid]/events/ratings?history=1m&null=false</tt> Returns all item ratings that have occurred within the past month, excluding any null ratings.

==Working with Events==
====Retrieve a Specific Event====
;<tt>GET /events/[eid]</tt>
:Retrieves the specified event.
: response example (JSON): <tt>{"eid":"945","type":"rating","uid":"516","iid":42,"timestamp":2005928682,"value":3.66}</tt>
:: '''timestamp''' represents the seconds since the [[Wikipedia: Unix time|Unix epoch]] (UTC). Implementations may provide additional attributes to support the user's local time.

====Remove a Specific Event====
;<tt>DELETE /events/[eid]</tt>
:Deletes the specified event from the server. Precise behavior will vary between implementations.

==Miscellaneous==
====Retrieve System Statistics====
;<tt>GET /statistics</tt>
:Retrieves general system-wide statistics.

== External links ==
* [https://github.com/igorbrigadir/Common-Recommender-REST-API Open API 3.0.0 Spec for the Common Recommender REST API]

[[Category: API]]

RecSysWiki:Current events

2020-07-24T13:37:17Z

IgorBrigadir: update events - recsyschallenge and recsys2020

''Feel free to add current/upcoming events about recommender systems here.''

__NOTOC__

== Ongoing ==

* 2020-07-08 [[Recommender_Systems_Challenge]]: [http://www.recsyschallenge.com/2020/#dates Paper Submission, contest is now completed.]

== Upcoming ==
* 2020-09-22: [https://recsys.acm.org/recsys20/dates/ ACM RecSys 2020]

[[Category: Event| ]]

RecSysWiki:Current events

2020-07-24T13:29:34Z

IgorBrigadir: /* Ongoing */ add ongoing event: recsyschallenge 2020

''Feel free to add current/upcoming events about recommender systems here.''

__NOTOC__

== Ongoing ==

2020-07-08 [http://www.recsyschallenge.com/2020/#dates RecSys Challenge 2020 Paper Submission, contest is now completed.]

== Upcoming ==
* September 15-19: [http://recsys.acm.org/recsys16 ACM RecSys 2016]

* September 05-08: [http://www.dexa.org/ecweb2016 17th International Conference on Electronic Commerce and Web Technologies - EC-Web 2016]

[[Category: Event| ]]

Recommender Systems Challenge

2020-07-24T12:33:37Z

IgorBrigadir: Add titles to links, fix dead link with archive.org and add challenges up to 2020

The '''Recommender Systems Challenge''' is the official challenge of the [[ACM RecSys]] conference series. The challenge started with the [[CAMRa 2010]] challenge at [[RecSys 2010]]. Since 2012, the challenges at RecSys have been labeled RecSysChallenge.

===External links===
* [http://recsys.acm.org/honors-and-awards/challenges/ List of RecSys Challenge winners]
* [http://www.dai-labor.de/camra2010/ CAMRa2010] Context-Aware Movie Recommendation
* [https://web.archive.org/web/20160310010222/http://2011.camrachallenge.com/ CAMRa2011] Context-Aware Movie Recommendation
* [http://2012.recsyschallenge.com RecSysChallenge 2012] Two tracks: CAMRa (Context-Aware Movie Recommendation) and ScienceRec (Scientific Paper Recommendation)
* [http://2013.recsyschallenge.com RecSysChallenge 2013] Yelp Business Rating Prediction
* [http://2014.recsyschallenge.com RecSysChallenge 2014] User Engagement as Evaluation using [[MovieTweetings]]
* [http://2015.recsyschallenge.com RecSysChallenge 2015] YooChoose e-commerce click and buy prediction
* [http://2016.recsyschallenge.com RecSysChallenge 2016] XING job posting recommendation
* [http://2017.recsyschallenge.com RecSysChallenge 2017] XING job posting recommendation in a cold-start setting.
* [http://2018.recsyschallenge.com RecSysChallenge 2018] Spotify automatic playlist continuation
* [http://2019.recsyschallenge.com RecSysChallenge 2019] Trivago session-based and context-aware accommodation recommendation
* [http://2020.recsyschallenge.com RecSysChallenge 2020] Twitter engagement prediction

[[Category:event]]
[[Category:competition]]

MovieTweetings

2020-07-24T12:22:38Z

IgorBrigadir: create redirect for MovieTweetings -> Movietweetings

#REDIRECT [[Movietweetings]]

Main Page

2020-06-22T09:33:04Z

IgorBrigadir: Remove missing number of views stat

{{DISPLAYTITLE:<span style="display:none">{{FULLPAGENAME}}</span>}}
<div id="mainpage">
</div>
__NOTOC__

{|style="width:100%;margin-top:+.9em;background-color:#fcfcfc;border:1px solid #ccc"
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<div style="font-size:162%;border:none;margin: 0;padding:.1em;color:#000">Welcome to the Recommender Systems Wiki (RecSysWiki) </div>
<div style="top:+0.2em;font-size: 95%">''sharing information on all aspects of [[Recommender System|Recommender Systems]]''</div>
<div id="articlecount" style="width:100%;text-align:center;font-size:85%;">'''{{NUMBEROFPAGES}}''' pages and '''{{NUMBEROFARTICLES}}''' articles, created by [[Special:ActiveUsers|{{NUMBEROFUSERS}} users]] as of {{CURRENTDAYNAME}}, {{CURRENTMONTHNAME}} {{CURRENTDAY}}, {{CURRENTYEAR}}</div>
<div style="width:100%;text-align:center;font-size:85%;">started on February 10th, 2011</div>
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[[RecSysWiki:About|This Wiki]] is about everything related to [[Recommender System|Recommender Systems]].

[[Special:UserLogin|Registration]] is open to anyone who wishes to contribute.


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{|width="100%" cellpadding="2" cellspacing="5" style="vertical-align:top;background-color:#f5fffa"
! <h2 style="margin:0;background-color:#cef2e0;font-size:120%;font-weight:bold;border:1px solid #a3bfb1;text-align:left;color:#000;padding:0.2em 0.4em;">Categories in RecSysWiki</h2>
|-
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* [[:Category:API|APIs]]
* [[:Category:Book|Books]]
* [[:Category:Class|Classes]]
* [[:Category:Company|Companies]]
* [[:Category:Competition|Competitions]]
* [[:Category:Conference|Conferences]]
* [[:Category:Dataset|Datasets]]
* [[:Category:Educational recommender systems|Educational Recommender Systems]]
* [[:Category:Evaluation|Evaluation]]
* [[:Category:Evaluation measure|Evaluation Measures]]
* [[:Category:Event|Events]]
* [[:Category:Job offer|Job Offers]]
* [[:Category:Journal|Journals]]
* [[:Category:List|Lists]]
* [[:Category:Literature|Literature]]
* [[:Category:Method|Methods]]
* [[:Category:Movie recommendation|Movie Recommendation]]
* [[:Category:Music recommendation|Music Recommendation]]
* [[:Category:Paper|Papers]]
* [[:Category:People|People]]
* [[:Category:Project|Projects]]
* [[:Category:Research group|Research Groups]]
* [[:Category:Software|Software]]
* [[:Category:Task|Task]]
* [[:Category:User-centric evaluation|User-centric evaluation]]
* [[:Category:Workshop|Workshops]]

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{| width="100%" cellpadding="2" cellspacing="5" style="vertical-align:top;background-color:#f5faff"
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<h2 style="margin:0;background-color:#cedff2;font-size:120%;font-weight:bold;border:1px solid #a3b0bf;text-align:left;color:#000;padding:0.2em 0.4em;">Information on RecSysWiki</h2>
|-
|style="color:#000"|
* [[:RecSysWiki:Current events| Current Events]]
* [[Special:Statistics|RecSysWiki statistics]]
* [[Special:AllPages|All pages]]
* [[Special:Categories|All categories]]
* [[Special:WantedPages|Wanted pages]]
* [[To Do List]] - ''please help by contributing''

<h2 style="margin:0;background-color:#cedff2;font-size:120%;font-weight:bold;border:1px solid #a3b0bf;text-align:left;color:#000;padding:0.2em 0.4em;">Recent additions and updates</h2>
|-
|style="color:#000"|

* [[Recommendation Datasets]] 
* [[Recommendation Software]] 
* [[List of recommender systems master's theses | Master's Theses]] 
* [[TagRec]] 
* [[CrowdRec]] 
* [[RecSysChallenge]] 
* [[LibRec]] 
* [[Test.fm]] 
* [[Okapi]] 
* [[ORP]] 
* [[RecSys-frontend]] 
* [[Dissertations]] 
* [[RiVal]] 
|-
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[[Category:RecSys Wiki Information]]

User:IgorBrigadir

2020-06-13T20:25:52Z

IgorBrigadir: Add Description

Senior Research Engineer at recsyslabs in the Insight Centre for Data Analytics, based in UCD, Ireland.