patricia-trie

问题 I have about 10,000 words used as a set of inverted indices to about 500,000 documents. Both are normalized so the index is a mapping of integers (word id) to a set of integers (ids of documents which contain the word). My prototype uses Python's set as the obvious data type. When I do a search for a document I find the list of N search words and their corresponding N sets. I want to return the set of documents in the intersection of those N sets. Python's "intersect" method is implemented as

问题 I'm attempting to implement a Patricia Trie with the methods addWord() , isWord() , and isPrefix() as a means to store a large dictionary of words for quick retrieval (including prefix search). I've read up on the concepts but they just aren't clarifying into an implementation. I want to know (in Java or Python code) how to implement the Trie, particularly the nodes (or should I implement it recursively). I saw one person who implemented it with an array of 26 child nodes set to null/None. Is

问题 I am implementing Patricia tries for IP prefix lookup, I could get the code working for complete key match, but facing problems with prefix search, when there are keys which are prefixes of other keys, like: 1.2.3.0 1.2.0.0 Can anyone help me with the algorithm for prefix searches in the above case Should I consider these as keys of separate length (i.e, /24 and 16) ? 回答1: Take a look at Net-Patricia. This is an implementation of a Patricia trie to look up IP addresses. The interface is perl,

问题 Are the trie and radix trie data structures the same thing? If they are same, then what is the meaning of radix trie (AKA Patricia trie)? 回答1: A radix tree is a compressed version of a trie. In a trie, on each edge you write a single letter, while in a PATRICIA tree (or radix tree) you store whole words. Now, assume you have the words hello , hat and have . To store them in a trie , it would look like: e - l - l - o / h - a - t \ v - e And you need nine nodes. I have placed the letters in the