我们可以使用Aho-Corasick算法来匹配多个模式组。在这个应用中，我们需要将每个模式组如图解压缩到类似trie的结构中。然后我们创建一个队列（queue）用于处理每一轮匹配。每个队列元素代表当前匹配到的位置和包含在某个模式组中的模式。 最后，我们使用自动机匹配算法在每个队列元素中使用匹配的模式组。其中还需要使用状态转移函数计算出下一个队列元素。整个匹配过程在每个队列上重复进行直到队列为空为止。下面是代码示例：

class ACNode:
    def __init__(self):
        self.fail = None
        self.paths = {}
        self.pattern_ids = []

def build_trie(patterns):
    root = ACNode()
    for idx, p in enumerate(patterns):
        node = root
        for c in p:
            node.paths[c] = node.paths.get(c, ACNode())
            node = node.paths[c]
        node.pattern_ids.append(idx)
    return root

def match(text, patterns):
    trie_root = build_trie(patterns)
    text_len = len(text)
    queue = [(trie_root, -1, set())]

    for i in range(text_len):
        new_queue = []
        for node, idx, matched_pattern_idx in queue:
            for c, child in node.paths.items():
                if c == text[i]:
                    new_idx = idx + 1
                else:
                    next_node = node.fail
                    while next_node and c not in next_node.paths:
                        next_node = next_node.fail
                    if next_node:
                        new_idx = 0
                        child = next_node.paths[c]
                    else:
                        new_idx = -1
                        child = trie_root

                new_matched_pattern_idx = matched_pattern_idx.union(child.pattern_ids)
                if child.pattern_ids:
                    new_queue.append((child, new_idx, new_matched_pattern_idx))

                if child.fail:
                    fail_node = child.fail
                    while fail_node:
                        new_matched_pattern_idx = matched_pattern_idx.union(fail_node.pattern_ids)
                        new_queue.append((fail_node, new_idx, new_matched_pattern_idx))
                        fail_node = fail_node.fail

        queue = new_queue
        if not queue:
            break

    return [matched_pattern_idx for node, idx, matched_pattern_idx in queue]