Zipf's law leads to Heaps' law: analyzing their relation in finite-size systems
Zipf's law and Heaps' law are observed in disparate complex systems. Of particular interests, these two laws often appear together. Many theoretical models and analyses are performed to understand their co-occurrence in real systems, but it still lacks a clear picture about their relation....
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description | Zipf's law and Heaps' law are observed in disparate complex systems. Of particular interests, these two laws often appear together. Many theoretical models and analyses are performed to understand their co-occurrence in real systems, but it still lacks a clear picture about their relation.
We show that the Heaps' law can be considered as a derivative phenomenon if the system obeys the Zipf's law. Furthermore, we refine the known approximate solution of the Heaps' exponent provided the Zipf's exponent. We show that the approximate solution is indeed an asymptotic solution for infinite systems, while in the finite-size system the Heaps' exponent is sensitive to the system size. Extensive empirical analysis on tens of disparate systems demonstrates that our refined results can better capture the relation between the Zipf's and Heaps' exponents.
The present analysis provides a clear picture about the relation between the Zipf's law and Heaps' law without the help of any specific stochastic model, namely the Heaps' law is indeed a derivative phenomenon from the Zipf's law. The presented numerical method gives considerably better estimation of the Heaps' exponent given the Zipf's exponent and the system size. Our analysis provides some insights and implications of real complex systems. For example, one can naturally obtained a better explanation of the accelerated growth of scale-free networks. |
doi_str_mv | 10.1371/journal.pone.0014139 |
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We show that the Heaps' law can be considered as a derivative phenomenon if the system obeys the Zipf's law. Furthermore, we refine the known approximate solution of the Heaps' exponent provided the Zipf's exponent. We show that the approximate solution is indeed an asymptotic solution for infinite systems, while in the finite-size system the Heaps' exponent is sensitive to the system size. Extensive empirical analysis on tens of disparate systems demonstrates that our refined results can better capture the relation between the Zipf's and Heaps' exponents.
The present analysis provides a clear picture about the relation between the Zipf's law and Heaps' law without the help of any specific stochastic model, namely the Heaps' law is indeed a derivative phenomenon from the Zipf's law. The presented numerical method gives considerably better estimation of the Heaps' exponent given the Zipf's exponent and the system size. Our analysis provides some insights and implications of real complex systems. For example, one can naturally obtained a better explanation of the accelerated growth of scale-free networks.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0014139</identifier><identifier>PMID: 21152034</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Analysis ; Biophysics - methods ; Complex systems ; Databases, Bibliographic ; Empirical analysis ; Influenza ; Keywords ; Language ; Laws, regulations and rules ; Linguistics ; Markov Chains ; Mathematical models ; Models, Statistical ; Natural language processing ; Numerical analysis ; Orthomyxoviridae - genetics ; Pandemics ; Physics ; Physics/Condensed Matter ; Physics/Interdisciplinary Physics ; Science ; Stochastic models ; Stochastic Processes ; Stochasticity ; Trade cycles ; Zipf's Law</subject><ispartof>PloS one, 2010-12, Vol.5 (12), p.e14139-e14139</ispartof><rights>COPYRIGHT 2010 Public Library of Science</rights><rights>2010 Lü et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Lü et al. 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c691t-f3db8beb0d76a0f77cf2e87fdd7fb31144d043952a90a7cfd4450b8f3b1b44983</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996287/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996287/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21152034$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lü, Linyuan</creatorcontrib><creatorcontrib>Zhang, Zi-Ke</creatorcontrib><creatorcontrib>Zhou, Tao</creatorcontrib><title>Zipf's law leads to Heaps' law: analyzing their relation in finite-size systems</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Zipf's law and Heaps' law are observed in disparate complex systems. Of particular interests, these two laws often appear together. Many theoretical models and analyses are performed to understand their co-occurrence in real systems, but it still lacks a clear picture about their relation.
We show that the Heaps' law can be considered as a derivative phenomenon if the system obeys the Zipf's law. Furthermore, we refine the known approximate solution of the Heaps' exponent provided the Zipf's exponent. We show that the approximate solution is indeed an asymptotic solution for infinite systems, while in the finite-size system the Heaps' exponent is sensitive to the system size. Extensive empirical analysis on tens of disparate systems demonstrates that our refined results can better capture the relation between the Zipf's and Heaps' exponents.
The present analysis provides a clear picture about the relation between the Zipf's law and Heaps' law without the help of any specific stochastic model, namely the Heaps' law is indeed a derivative phenomenon from the Zipf's law. The presented numerical method gives considerably better estimation of the Heaps' exponent given the Zipf's exponent and the system size. Our analysis provides some insights and implications of real complex systems. For example, one can naturally obtained a better explanation of the accelerated growth of scale-free networks.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Biophysics - methods</subject><subject>Complex systems</subject><subject>Databases, Bibliographic</subject><subject>Empirical analysis</subject><subject>Influenza</subject><subject>Keywords</subject><subject>Language</subject><subject>Laws, regulations and rules</subject><subject>Linguistics</subject><subject>Markov Chains</subject><subject>Mathematical models</subject><subject>Models, Statistical</subject><subject>Natural language processing</subject><subject>Numerical analysis</subject><subject>Orthomyxoviridae - genetics</subject><subject>Pandemics</subject><subject>Physics</subject><subject>Physics/Condensed Matter</subject><subject>Physics/Interdisciplinary Physics</subject><subject>Science</subject><subject>Stochastic models</subject><subject>Stochastic Processes</subject><subject>Stochasticity</subject><subject>Trade cycles</subject><subject>Zipf's Law</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNkl2LEzEUhgdR3HX1H4gOCBYvWvM1M4kXwrKoW1go-HXhTchMTtqUdNKdZNTurze1s0tH9kJykXDOc96TnLxZ9hyjGaYVfrv2fdcqN9v6FmYIYYapeJCdYkHJtCSIPjw6n2RPQlgjVFBelo-zE4JxkcLsNFv8sFszCblTv3IHSoc8-vwS1DZM9rF3uUo9dje2XeZxBbbLO3AqWt_mts2NbW2EabA3kIddiLAJT7NHRrkAz4b9LPv28cPXi8vp1eLT_OL8atqUAsepobrmNdRIV6VCpqoaQ4BXRuvK1BRjxjRiVBRECaRSUjNWoJobWuOaMcHpWfbyoLt1PshhFkFiirmgghcoEfMDob1ay21nN6rbSa-s_Bvw3VKqLtrGgSxAU0QEAKkFEzWtFVSKNILSJnVjOmm9H7r19QZ0A23slBuJjjOtXcml_ymJECXhVRKYDAKdv-4hRLmxoQHnVAu-D5ITVPGSE5bIV_-Q9z9uoJYq3d-2xqe2zV5TnrOKJqEklqjZPVRaGja2Sb4xNsVHBW9GBYmJ8DsuVR-CnH_5_P_s4vuYfX3ErkC5uAre9XsjhTHIDmDT-RA6MHczxkjubX87Dbm3vRxsn8peHP_PXdGtz-kffC38pg</recordid><startdate>20101202</startdate><enddate>20101202</enddate><creator>Lü, Linyuan</creator><creator>Zhang, Zi-Ke</creator><creator>Zhou, Tao</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20101202</creationdate><title>Zipf's law leads to Heaps' law: analyzing their relation in finite-size systems</title><author>Lü, Linyuan ; Zhang, Zi-Ke ; Zhou, Tao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c691t-f3db8beb0d76a0f77cf2e87fdd7fb31144d043952a90a7cfd4450b8f3b1b44983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Algorithms</topic><topic>Analysis</topic><topic>Biophysics - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lü, Linyuan</au><au>Zhang, Zi-Ke</au><au>Zhou, Tao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Zipf's law leads to Heaps' law: analyzing their relation in finite-size systems</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2010-12-02</date><risdate>2010</risdate><volume>5</volume><issue>12</issue><spage>e14139</spage><epage>e14139</epage><pages>e14139-e14139</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Zipf's law and Heaps' law are observed in disparate complex systems. Of particular interests, these two laws often appear together. Many theoretical models and analyses are performed to understand their co-occurrence in real systems, but it still lacks a clear picture about their relation.
We show that the Heaps' law can be considered as a derivative phenomenon if the system obeys the Zipf's law. Furthermore, we refine the known approximate solution of the Heaps' exponent provided the Zipf's exponent. We show that the approximate solution is indeed an asymptotic solution for infinite systems, while in the finite-size system the Heaps' exponent is sensitive to the system size. Extensive empirical analysis on tens of disparate systems demonstrates that our refined results can better capture the relation between the Zipf's and Heaps' exponents.
The present analysis provides a clear picture about the relation between the Zipf's law and Heaps' law without the help of any specific stochastic model, namely the Heaps' law is indeed a derivative phenomenon from the Zipf's law. The presented numerical method gives considerably better estimation of the Heaps' exponent given the Zipf's exponent and the system size. Our analysis provides some insights and implications of real complex systems. For example, one can naturally obtained a better explanation of the accelerated growth of scale-free networks.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>21152034</pmid><doi>10.1371/journal.pone.0014139</doi><tpages>e14139</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Analysis Biophysics - methods Complex systems Databases, Bibliographic Empirical analysis Influenza Keywords Language Laws, regulations and rules Linguistics Markov Chains Mathematical models Models, Statistical Natural language processing Numerical analysis Orthomyxoviridae - genetics Pandemics Physics Physics/Condensed Matter Physics/Interdisciplinary Physics Science Stochastic models Stochastic Processes Stochasticity Trade cycles Zipf's Law |
title | Zipf's law leads to Heaps' law: analyzing their relation in finite-size systems |
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