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A performance prediction model for bibliographic search using multiple regression technique

Syed Muhammed Asad

1973
Bibliographical Searching Searching Bibliographical
Wait Until Dark
3.6 513 votes
The Space Between Us
3.5 3K votes
Hang 'em High
3.4 743 votes
The Client
3.3 2K votes
The Lady Vanishes
3.7 899 votes
Bicycle Thieves
4.1 3K votes
Pokémon: The First Movie
3.4 2K votes
The Love Witch
3.2 518 votes
Nine
2.8 581 votes
Taken
3.7 12K votes
Lake Mungo
3.1 527 votes
Before I Go to Sleep
3.2 2K votes
Fire in the Sky
3.3 571 votes
I See You !!
3.5 2K votes
The Animal Kingdom
3.5 643 votes
Time Trap
3.1 2K votes
Labor Day
3.5 2K votes
Father Figures
2.9 618 votes
Slow West
3.3 955 votes
Gone Girl
3.9 19K votes
Coming to America
3.5 5K votes
Joe
3.3 912 votes
Moonrise Kingdom
3.8 6K votes
Philomena
3.7 2K votes
San Andreas
3.1 9K votes
The Lives of Others
4.0 4K votes
Austin Powers: The Spy Who Shagged Me
3.1 4K votes
Catwoman
2.3 4K votes
Eastern Promises
3.7 4K votes
Fracture
3.6 4K votes
Bram Stoker's Dracula
3.8 6K votes
The Great Dictator
4.2 4K votes
Lethal Weapon 2
3.5 4K votes
Battle Royale
3.6 4K votes
Austin Powers: International Man of Mystery
3.3 4K votes
Twister
3.3 4K votes
Natural Born Killers
3.5 4K votes
Thelma & Louise
3.8 4K votes
Stargate
3.5 4K votes
Into the Wild
3.9 10K votes
Crash
3.6 4K votes
Some Like It Hot
4.0 4K votes
The Elephant Man
4.0 4K votes
Magnolia
3.9 4K votes
The Darjeeling Limited
3.6 4K votes
Nausicaä of the Valley of the Wind
4.0 4K votes
Dr. No
3.5 4K votes
3:10 to Yuma
3.6 4K votes