from math import sqrt


oceniPoKorisnici = {
    'Lisa Rose': {'Catch Me If You Can': 3.0, 'Snakes on a Plane': 3.5, 'Superman Returns': 3.5,
                  'You, Me and Dupree': 2.5, 'The Night Listener': 3.0, 'Snitch': 3.0},
    'Gene Seymour': {'Lady in the Water': 3.0, 'Snakes on a Plane': 3.5, 'Just My Luck': 1.5, 'The Night Listener': 3.0,
                     'You, Me and Dupree': 3.5},
    'Michael Phillips': {'Catch Me If You Can': 2.5, 'Lady in the Water': 2.5, 'Superman Returns': 3.5,
                         'The Night Listener': 4.0, 'Snitch': 2.0},
    'Claudia Puig': {'Snakes on a Plane': 3.5, 'Just My Luck': 3.0, 'The Night Listener': 4.5, 'Superman Returns': 4.0,
                     'You, Me and Dupree': 2.5},
    'Mick LaSalle': {'Lady in the Water': 3.0, 'Snakes on a Plane': 4.0, 'Just My Luck': 2.0, 'Superman Returns': 3.0,
                     'You, Me and Dupree': 2.0},
    'Jack Matthews': {'Catch Me If You Can': 4.5, 'Lady in the Water': 3.0, 'Snakes on a Plane': 4.0,
                      'The Night Listener': 3.0, 'Superman Returns': 5.0, 'You, Me and Dupree': 3.5, 'Snitch': 4.5},
    'Toby': {'Snakes on a Plane': 4.5, 'Snitch': 5.0},
    'Michelle Nichols': {'Just My Luck': 1.0, 'The Night Listener': 4.5, 'You, Me and Dupree': 3.5,
                         'Catch Me If You Can': 2.5, 'Snakes on a Plane': 3.0},
    'Gary Coleman': {'Lady in the Water': 1.0, 'Catch Me If You Can': 1.5, 'Superman Returns': 1.5,
                     'You, Me and Dupree': 2.0},
    'Larry': {'Lady in the Water': 3.0, 'Just My Luck': 3.5, 'Snitch': 1.5, 'The Night Listener': 3.5}
}


# Vrakja merka za slicnost bazirana na rastojanieto za person1 i person2
def sim_distance(prefs, person1, person2):
    # Se pravi lista na zaednicki predmeti (filmovi)
    si = {}
    for item in prefs[person1]:
        if item in prefs[person2]:
            si[item] = 1
    # ako nemaat zaednicki rejtinzi, vrati 0
    if len(si) == 0:
        return 0
    # Soberi gi kvadratite na site razliki
    sum_of_squares = sum([pow(prefs[person1][item] - prefs[person2][item], 2)
    for item in prefs[person1] if item in prefs[person2]])
    return round(1 / (1 + sqrt(sum_of_squares)),3)


def sim_pearson(oceni, person1, person2):
    zaednicki = {}
    for item in oceni[person1]:
        if item in oceni[person2]:
            zaednicki[item] = 1

    n = len(zaednicki)

    if n == 0:
        return [0, 0]

    sum1 = 0
    sum2 = 0

    sum1Sq = 0
    sum2Sq = 0

    pSum = 0
    for item in zaednicki.keys():
        ocena1 = oceni[person1][item]
        ocena2 = oceni[person2][item]
        sum1 += ocena1
        sum1Sq += ocena1 ** 2
        sum2 += ocena2
        sum2Sq += ocena2 ** 2
        pSum += ocena1 * ocena2

    # Presmetaj go koeficientot na korelacija
    num = pSum - sum1 * sum2 / n
    den = sqrt((sum1Sq - pow(sum1, 2) / n) * (sum2Sq - pow(sum2, 2) / n))
    if den == 0:
        return [0, 0]

    r = num / den
    return round(r, 3), n



def TabelaNaSlicniKorisnici(oceni):
    result = {}
    for x in oceni:
        for y in oceni:
            if x != y:
                if x not in result.keys():
                   result[x]={}
                pearson = sim_pearson(oceni, x, y)[0]
                evklidovo = sim_distance(oceni, x, y)
                zaedncki = sim_pearson(oceni, x, y)[1]
                result[x][y] = (evklidovo, pearson, zaedncki)
    return result


if __name__ == "__main__":
    korisnik1 = input()
    korisnik2 = input()
    # korisnik1='Mick LaSalle'
    # korisnik2='Lisa Rose'
    # print oceniPoKorisnici
    tabela = TabelaNaSlicniKorisnici(oceniPoKorisnici)
    #print tabela
    print tabela[korisnik1][korisnik2]