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Support Estimation in Frequent Itemset Mining by Locality Sensitive Hashing
2019
Lernen, Wissen, Daten, Analysen
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The support of a query itemset is then estimated by means of these summaries. ...
The main computational eort in generating all frequent itemsets in a transactional database is in the step of deciding whether an itemset is frequent, or not. ...
frequent itemset mining algorithms. ...
dblp:conf/lwa/Pick0W19
fatcat:aka6cmx6ejhdlibjiqwqpa2u5a
Detecting Changes in User-Centered Music Query Streams
2006
2006 IEEE International Conference on Multimedia and Expo
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In this paper, we propose an efficient algorithm, called MQSchange (changes of Music Query Streams), to detect the changes of maximal melody structures in user-centered music query streams. ...
Experiments show that MQS-change algorithm is an online, single-pass approach to detect the changes of music melody structures over continuous music query streams. ...
This motivates the design for inmemory summary data structure with small memory footprints that can support both one-time and continuous queries. ...
doi:10.1109/icme.2006.262946
dblp:conf/icmcs/LiSL06
fatcat:q5zrecnw55b4risgbozxtpenue
Dynamic index selection in data warehouses
2007
2007 Innovations in Information Technologies (IIT)
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In this paper, we present an automatic, dynamic index selection method for data warehouses that is based on incremental frequent itemset mining from a given query workload. ...
Analytical queries defined on data warehouses are complex and use several join operations that are very costly, especially when run on very large data volumes. ...
Incremental frequent itemset mining Many algorithms have been proposed in the literature for incrementally mining frequent itemsets. ...
doi:10.1109/iit.2007.4430394
fatcat:rhepubhyrjg75mkpwr65muhvxq
Itemset Support Queries Using Frequent Itemsets and Their Condensed Representations
[chapter]
2006
Lecture Notes in Computer Science
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The purpose of this paper is two-fold: First, we give efficient algorithms for answering itemset support queries for collections of itemsets from various representations of the frequency information. ...
Second, we evaluate the usefulness of condensed representations of frequent itemsets to answer itemset support queries using the proposed query algorithms and index structures. ...
Frequent itemset mining has been a central issue in data mining since its introduction almost 15 years ago [1] , many efficient algorithms for frequent itemset mining have been proposed [2] [3] [4] , ...
doi:10.1007/11893318_18
fatcat:lj5xnzyksze2rd4xj5mtb22d74
Incremental Association Rule Mining Using Materialized Data Mining Views
[chapter]
2004
Lecture Notes in Computer Science
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mining queries. ...
Users issue series of similar queries until they receive satisfying results, yet currently available data mining systems do not support iterative processing of data mining queries and do not allow to re-use ...
These candidate itemsets are created by joining LNB with L 1 (extending every new frequent itemset with a frequent 1-itemset) and by joining L with LNB 1 (extending every frequent itemset with a frequent ...
doi:10.1007/978-3-540-30198-1_9
fatcat:6qer3c5g7jf4tgdm6cnxhc2bwm
Quantifying the informativeness for biomedical literature summarization: An itemset mining method
2017
Computer Methods and Programs in Biomedicine
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2016 pre-print arXiv:1609.03067v1 fatcat:a6omrt4bhjc7pkebm5cp3rzrjyOther Versions
The employed itemset mining algorithm extracts a set of frequent itemsets containing correlated and recurrent concepts of the input document. ...
Then, it discovers the essential subtopics of the text using a data mining technique, namely itemset mining, and constructs the summarization model. ...
Mode of availability The Java source code of the itemset-based biomedical text summarizer and its documentation are accessible at http://dkr.iut.ac.ir/content/code-itemset-based-summarizer. ...
doi:10.1016/j.cmpb.2017.05.011
pmid:28688492
fatcat:abqhm7ecpfhytavgl6tv4whe4e
Query-based summarization using MDL principle
2017
Proceedings of the MultiLing 2017 Workshop on Summarization and Summary Evaluation Across Source Types and Genres
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A summary is extracted by selecting sentences that best cover query-related frequent word sets. ...
The key idea of our approach is to select frequent word sets related to a given query that compress document sentences better and therefore describe the document better. ...
In this work, we use the Apriori-TID algorithm for frequent itemset mining. ...
doi:10.18653/v1/w17-1004
dblp:conf/acl-multiling/LitvakV17
fatcat:ra3ptucrq5dgbhpv6xaa7ybumy
Model-Independent Bounding of the Supports of Boolean Formulae in Binary Data
[chapter]
2004
Lecture Notes in Computer Science
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For example, when mining frequent itemsets, we know that the support of any infrequent set lies beneath the frequency threshold. ...
Data mining algorithms such as the Apriori method for finding frequent sets in sparse binary data can be used for efficient computation of a large number of summaries from huge data sets. ...
doi:10.1007/978-3-540-44497-8_12
fatcat:a44zwr5vnrdqfi27q75fhzjp7i
An Intersection Cache Based on Frequent Itemset Mining in Large Scale Search Engines
2015
2015 Third IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb)
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In TLMCA, we introduce an intersection cache data selection policy based on the Top-N frequent itemset mining, and design an intersection cache data replacement policy based on incremental frequent itemset ...
However, they cannot perform well with long queries. The policies used in intersection cache are inefficient with poor flexibility for different applications. ...
AN INTERSECTION CACHE DATA STRATEGY BASED ON FREQUENT ITEMSET MINING In TLMCA, we design a Top-N frequent itemset mining algorithm based on FP-Growth for our purpose. ...
doi:10.1109/hotweb.2015.17
dblp:conf/hotweb/ZhouLDXX15
fatcat:j7tgqlqflfbfjmshlpt53dfjsy
Optimization of association rule mining
2015
2015 Internet Technologies and Applications (ITA)
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Given a localized mining query, our CO-LARM query optimizer takes a cost-based approach to identify the best strategy for execution. ...
We analytically and experimentally demonstrate that different execution strategies are effective for different query scenarios. ...
Table 4 : 4 Summary of the six mining plans.LEMMA 4.5. ...
doi:10.1109/itecha.2015.7317409
fatcat:dqlo2u3lmjfbpc4cjlusgh64hy
On efficiently summarizing categorical databases
2005
Knowledge and Information Systems
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Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. ...
for clustering. ...
some studies have also demonstrated the usefulness of frequent itemset mining in serving as a condensed representation of the input data in order for answering various types of queries [8, 22] , and the ...
doi:10.1007/s10115-005-0216-7
fatcat:kojdvgqlivc7nizel7twtslswa
MaxPart: An Efficient Search-Space Pruning Approach to Vertical Partitioning
2018
Computing and informatics
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In this paper, an approach based on maximal frequent itemsets to vertical partitioning is proposed to efficiently search for an optimized solution by judiciously pruning the potential search space. ...
However, such fragments can directly and efficiently be achieved by the use of maximal frequent itemsets. ...
for mining maximal frequent itemsets. ...
doi:10.4149/cai_2018_4_915
fatcat:424mxlpgyfaf5gjdlae2q4aw6a
Incremental Data Mining Using Concurrent Online Refresh of Materialized Data Mining Views
[chapter]
2005
Lecture Notes in Computer Science
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This model of processing is most suitable for incremental mining algorithms that reuse the results of previous queries when answering a given query. ...
We present the framework for the integration of data warehouse refresh process with the maintenance of materialized data mining views. ...
The table contains both frequent itemsets constituting the answer to the data mining query, and the negative border of the collection of frequent itemsets. ...
doi:10.1007/11546849_29
fatcat:i72raoykcjac5o2yibc2k4oy4i
Space Lower Bounds for Itemset Frequency Sketches
2016
Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems - PODS '16
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Given a database, computing the fraction of rows that contain a query itemset or determining whether this fraction is above some threshold are fundamental operations in data mining. ...
For many seemingly similar problems there are better sketching algorithms than uniform sampling. In this paper we show that for itemset frequency sketching this is not the case. ...
Introduction Identifying frequent itemsets is one of the most basic and well-studied problems in data mining. ...
doi:10.1145/2902251.2902278
dblp:conf/pods/LibertyMTU16
fatcat:ex7vgevns5aqljvc2elcruyqki
Provenance for Data Mining
2013
Workshop on the Theory and Practice of Provenance
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To illustrate our ideas, we present a more detailed discussion of these concepts for two typical data mining algorithms: frequent itemset mining and multi-dimensional scaling. ...
We analyze the differences between database, workflow, and data mining provenance, suggest new types of provenance, and identify new usecases for provenance in data mining. ...
Frequent Itemset Mining One of the most prevalent data mining tasks is Frequent Itemset Mining (FIM). ...
dblp:conf/tapp/GlavicSAM13
fatcat:3wv5mwjzmng7lp7uxp7tbgaqmq
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