import sys
input = sys.stdin.readline
sys.setrecursionlimit(1000000)

from collections import defaultdict
from collections import deque
import heapq

MOD = 998244353

def DD(arg): return defaultdict(arg)

def inv(n): return pow(n, MOD-2, MOD)

kaijo_memo = []
def kaijo(n):
  if(len(kaijo_memo) > n): return kaijo_memo[n]
  if(len(kaijo_memo) == 0): kaijo_memo.append(1)
  while(len(kaijo_memo) <= n): kaijo_memo.append(kaijo_memo[-1] * len(kaijo_memo) % MOD)
  return kaijo_memo[n]

gyaku_kaijo_memo = []
def gyaku_kaijo(n):
  if(len(gyaku_kaijo_memo) > n): return gyaku_kaijo_memo[n]
  if(len(gyaku_kaijo_memo) == 0): gyaku_kaijo_memo.append(1)
  while(len(gyaku_kaijo_memo) <= n): gyaku_kaijo_memo.append(gyaku_kaijo_memo[-1] * pow(len(gyaku_kaijo_memo),MOD-2,MOD) % MOD)
  return gyaku_kaijo_memo[n]

import numpy as np

def fft_convolve(f, g):
    """
    数列 (多項式) f, g の畳み込みの計算．上下 15 bitずつ分けて計算することで，
    30 bit以下の整数，長さ 250000 程度の数列での計算が正確に行える．
    """
    Lf, Lg = f.shape[-1], g.shape[-1]
    Lg = g.shape[-1]
    L = Lf + Lg - 1
    fft_len = 1 << L.bit_length()
    fh, fl = f >> 15, f & (1 << 15) - 1
    gh, gl = g >> 15, g & (1 << 15) - 1
 
    def conv(f, g):
        Ff = np.fft.rfft(f, fft_len)
        Fg = np.fft.rfft(g, fft_len)
        h = np.fft.irfft(Ff * Fg)
        return np.rint(h)[..., :L].astype(np.int64) % MOD
 
    x = conv(fl, gl)
    z = conv(fh, gh)
    y = conv(fl + fh, gl + gh) - x - z
    return (x + (y << 15) + (z << 30)) % MOD
  
N = int(input())

nokori = [1]
for n in range(1,2*N+10):
  nokori.append((nokori[-1]*(2*n-1)*(2*n)*inv(2)*inv(n))%MOD)

dic = DD(int)
for _ in range(N*2):
  dic[int(input())] += 1
A = [dic[k] for k in dic]
  
P = []
for a in A:
  temp = 1
  count = 0
  P.append([temp])
  while a >= 2:
    temp *= a*(a-1)//2
    temp %= MOD
    count += 1
    P[-1].append((temp*gyaku_kaijo(count))%MOD)
    a -= 2


data = [np.array(p) for p in P]
Q = []
for i in range(len(data)):
  heapq.heappush(Q,(len(data[i]),i))

while len(Q)>1:
  _,p = heapq.heappop(Q)
  _,q = heapq.heappop(Q)
  temp = fft_convolve(data[p], data[q])
  data.append(temp)
  heapq.heappush(Q,(len(temp),len(data)-1))
Q = list(data[-1])

ans = 0
M = len(Q)

def sign(x):
  if x%2: return -1
  else: return 1

for i in range(M):
  ans += sign(i) * Q[i] * nokori[N-i]
  ans %= MOD
  
print(ans)