Information-Retrieval

Information Retrieval and Data Mining

submit

Expriment 1 (2021.9.14 -- 2021.10.13)

在tweets数据集上构建inverted index

实现Boolean Retrieval Model,使用TREC 2014 test topics进行测试 https://trec.nist.gov/data/microblog/2014/topics.desc.MB171-225.txt

Boolean Retrieval Model:

Input:a query (like Ron and Weasley)

Output: print the qualified tweets.

支持and, or ,not(查询优化可以选做)

对于tweets与queries使用相同的预处理

Expriment 2 (2021.10.13 -- 2021.11.9)

在Expriment 1 的基础上实现最基本的Ranked retrieval model

• Input: a query (like Ron and Weasley)

• Output: return the top K (eg., K=100) relevant tweets.

使用SMART notation: lnc.ltn

Document: logarithmic tf (l as first character), no idf and cosine normalization

Query: logarithmic tf (l in leftmost column), idf (t in second column), no normalization

改进inverted index

在Dictionary中存储每个term的DF

在posting list中存储term在每个doc中的TF with pairs (docID, tf)

选做：支持所有的SMART Notations

Expriment 3 (2021.11.9 -- 2021.12.8)

实现以下指标评价，并对Experiment2的检索结果进行评价

Mean Average Precision (MAP)

Mean Reciprocal Rank (MRR)

Normalized Discounted Cumulative Gain (NDCG)