
If You Like Someone Like You(2007)
Based on real preference data from thousands of voters, here's what fans of Someone Like You also love.
66 connections found
#1109xKate & Leopold
2001Wo zhi nv ren xin
2011
#384xSomething's Gotta Give
2003
#484xNo Reservations
2007
#583xBecause I Said So
2007
#681xRunaway Bride
1999Wo zui hao peng you de hun li
2016
#878xThe Wedding Date
2005
#976xWhile You Were Sleeping
1995
#1072xTwo Weeks Notice
2002
#1171xRaising Helen
2004
#1269xChasing Liberty
2004
#1366xThe Lake House
2006
#1464xLeap Year
2010The Back-up Plan
2010
#1662xJust Like Heaven
2005
#1761xThe Wedding Planner
2001
#1861xSerendipity
2001
#1959xFailure to Launch
2006
#2058xWhen in Rome
2010
#2158xSweet Home Alabama
2002
#2257xMonster-in-Law
2005
#2357xMade of Honor
2008
#2455xMaid in Manhattan
2002
#2554xThe Perfect Man
2005
#2651xYou've Got Mail
1998
#2751xSleepless in Seattle
1993
#2845xNever Been Kissed
1999
#2944xThe Other Woman
2014Life as We Know It
2010
#3141xDefinitely, Maybe
2008
#3239xHe's Just Not That Into You
2009
#3338xSydney White
2007
#3438xThe Ugly Truth
2009
#3538xShe's All That
1999
#3638xWhat Happens in Vegas
2008
#3738xNo Strings Attached
2011
#3837xThe Sisterhood of the Traveling Pants
2005
#3936xMiss Congeniality
2000
#4035xLetters to Juliet
2010
#4135xNotting Hill
1999
#4235xConfessions of a Shopaholic
2009
#4334xThe Princess Diaries 2: Royal Engagement
2004
#4434xWhat a Girl Wants
2003
#4533xThe Holiday
2006
#4633xHow to Lose a Guy in 10 Days
2003
#4733xBride Wars
2009
#4832x27 Dresses
2008
#4930xThe Vow
2012
#5030xBridget Jones's Diary
2001
#5129xPretty Woman
1990
#5227xA Cinderella Story
2004
#5327xThe Proposal
2009
#5426x13 Going on 30
2004
#5524xA Walk to Remember
2002
#5623xThe Princess Diaries
2001
#5723xFreaky Friday
2003
#5822xFriends with Benefits
2011
#5922xShe's the Man
2006
#6018xThe Devil Wears Prada
2006
#6118xLegally Blonde
2001
#6212xThe Notebook
2004
#6311x10 Things I Hate About You
1999
#649.9xEasy A
2010
#658.7xHow to Train Your Dragon
2010
#662.9xInception
2010How does this work?
These recommendations are based on real voting data, not algorithms. When thousands of people vote on their favorites, patterns emerge — people who love Someone Like You consistently tend to also love certain other things. The "strength" score shows how much more likely fans of Someone Like You are to enjoy each recommendation compared to the average person.
Unlike algorithmic recommendations, these connections come from actual human preferences. A high strength score means the connection is genuine — not just because two items share a category, but because the same people genuinely love both.