@inproceedings{5c24aa66979d4db3aa977abba1abe997,
title = "Information retrieval with time series query",
abstract = "We study a novel information retrieval problem, where the query is a time series for a given time period, and the retrieval task is to find relevant documents in a text collection of the same time period, which contain topics that are correlated with the query time series. This retrieval problem arises in many text mining applications where there is a need to analyze text data in order to discover potentially causal topics. To solve this problem, we propose and study multiple retrieval algorithms that use the general idea of ranking text documents based on how well their terms are correlated with the query time series. Experiment results show that the proposed retrieval algorithm can effectively help users find documents that are relevant to the time series queries, which can help users analyze the variation patterns of the time series.",
keywords = "Information retrieval, Text stream, Time series query",
author = "Kim, {Hyun Duk} and Danila Nikitin and Zhai, {Cheng Xiang} and Malu Castellanos and Meichun Hsu",
year = "2013",
doi = "10.1145/2499178.2499195",
language = "English (US)",
isbn = "9781450321075",
series = "ACM International Conference Proceeding Series",
pages = "56--63",
booktitle = "International Conference on the Theory of Information Retrieval, ICTIR 2013 Proceedings",
note = "4th International Conference on the Theory of Information Retrieval, ICTIR 2013 ; Conference date: 29-09-2013 Through 02-10-2013",
}