research-article

Functionality-based clustering using short textual description: helping users to find apps installed on their mobile device

Authors:

David Lavid Ben Lulu,

Tsvi KuflikAuthors Info & Claims

IUI '13: Proceedings of the 2013 international conference on Intelligent user interfaces

Pages 297 - 306

https://doi.org/10.1145/2449396.2449434

Published: 19 March 2013 Publication History

Abstract

In recent years, we have witnessed the incredible popularity and widespread adoption of mobile devices. Millions of Apps are being developed and downloaded by users at an amazing rate. These are multi-feature Apps that address a broad range of needs and functions. Nowadays, every user has dozens of Apps on his mobile device. As time goes on, it becomes more and more difficult simply to find the desired App among those that are installed on the mobile device. In spite of several attempts to address the problem, no good solution for this increasing problem has yet been found. In this paper we suggest the use of unsupervised machine learning for clustering Apps based on their functionality, to allow users to access them easily. The functionality is elicited from their description as retrieved from various App stores and enriched by content from professional blogs. The Apps are clustered and grouped according to their functionality and presented hierarchically to the user in order to facilitate the search on the small screen of the mobile device.

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Cited By

Flondor EFrincu M(2023)Fine-Grained Categorization of Mobile Applications Through Semantic Similarity Techniques for Apps ClassificationSimilarity Search and Applications10.1007/978-3-031-46994-7_7(79-87)Online publication date: 27-Oct-2023
https://doi.org/10.1007/978-3-031-46994-7_7
Ebrahimi FTushev MMahmoud A(2021)Classifying Mobile Applications Using Word EmbeddingsACM Transactions on Software Engineering and Methodology10.1145/347482731:2(1-30)Online publication date: 17-Nov-2021
https://dl.acm.org/doi/10.1145/3474827
Uddin MHe QHan JChua C(2021)Mining Cross-Domain Apps for Software Evolution: A Feature-based Approach2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE)10.1109/ASE51524.2021.9678514(743-755)Online publication date: Nov-2021
https://doi.org/10.1109/ASE51524.2021.9678514
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Index Terms

Functionality-based clustering using short textual description: helping users to find apps installed on their mobile device
1. Human-centered computing
  1. Human computer interaction (HCI)
2. Information systems
  1. Information retrieval
    1. Document representation

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cover image ACM Conferences

IUI '13: Proceedings of the 2013 international conference on Intelligent user interfaces

March 2013

470 pages

ISBN:9781450319652

DOI:10.1145/2449396

General Chair:
Jihie Kim
University of Southern California, USA
,
Program Chairs:
Jeffrey Nichols
IBM Research -- Almaden, USA
,
Pedro Szekely
University of Southern California, USA

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 19 March 2013

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March 19 - 22, 2013

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IUI '13 Paper Acceptance Rate 43 of 192 submissions, 22%;

Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

Flondor EFrincu M(2023)Fine-Grained Categorization of Mobile Applications Through Semantic Similarity Techniques for Apps ClassificationSimilarity Search and Applications10.1007/978-3-031-46994-7_7(79-87)Online publication date: 27-Oct-2023
https://doi.org/10.1007/978-3-031-46994-7_7
Ebrahimi FTushev MMahmoud A(2021)Classifying Mobile Applications Using Word EmbeddingsACM Transactions on Software Engineering and Methodology10.1145/347482731:2(1-30)Online publication date: 17-Nov-2021
https://dl.acm.org/doi/10.1145/3474827
Uddin MHe QHan JChua C(2021)Mining Cross-Domain Apps for Software Evolution: A Feature-based Approach2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE)10.1109/ASE51524.2021.9678514(743-755)Online publication date: Nov-2021
https://doi.org/10.1109/ASE51524.2021.9678514
Bello-Jiménez LEscobar-Velásquez CMojica-Hanke ACortés-Fernández SLinares-Vásquez M(2020)Hall-of-AppsProceedings of the 17th International Conference on Mining Software Repositories10.1145/3379597.3387497(568-572)Online publication date: 29-Jun-2020
https://dl.acm.org/doi/10.1145/3379597.3387497
Yang JMa JHoward S(2019)Usage profiling from mobile applications: A case study of online activity for Australian primary schoolsKnowledge-Based Systems10.1016/j.knosys.2019.105214Online publication date: Nov-2019
https://doi.org/10.1016/j.knosys.2019.105214
Al-Subaihin ASarro FBlack SCapra L(2019)Empirical comparison of text-based mobile apps similarity measurement techniquesEmpirical Software Engineering10.1007/s10664-019-09726-5Online publication date: 24-Jun-2019
https://doi.org/10.1007/s10664-019-09726-5
Zhang CMark GFussell SLampe Cschraefel mHourcade JAppert CWigdor D(2017)Improving App Look up speed on Mobile via User-defined Touch GestureProceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems10.1145/3027063.3048419(196-201)Online publication date: 6-May-2017
https://dl.acm.org/doi/10.1145/3027063.3048419
Martin WSarro FJia YZhang YHarman M(2017)A Survey of App Store Analysis for Software EngineeringIEEE Transactions on Software Engineering10.1109/TSE.2016.263068943:9(817-847)Online publication date: 1-Sep-2017
https://doi.org/10.1109/TSE.2016.2630689
Johann TStanik CB. AMaalej W(2017)SAFE: A Simple Approach for Feature Extraction from App Descriptions and App Reviews2017 IEEE 25th International Requirements Engineering Conference (RE)10.1109/RE.2017.71(21-30)Online publication date: Sep-2017
https://doi.org/10.1109/RE.2017.71
Ali MJoorabchi MMesbah AGrundy JHalfond WBuhnova BAutili MMuccini H(2017)Same app, different app storesProceedings of the 4th International Conference on Mobile Software Engineering and Systems10.1109/MOBILESoft.2017.3(79-90)Online publication date: 20-May-2017
https://dl.acm.org/doi/10.1109/MOBILESoft.2017.3
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