A Critique Empirical Evaluation of Relevance Computation for Focused Web Crawlers

Mary, Joe Dhanith Pal Nesamony Rose; Balasubramanian, Surendiran; Raj, Raja Soosaimarian Peter

doi:10.1590/1678-4324-2021210223

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Review - Engineering, Technology and Techniques • Braz. arch. biol. technol. 64 • 2021 • https://doi.org/10.1590/1678-4324-2021210223 copy

A Critique Empirical Evaluation of Relevance Computation for Focused Web Crawlers

Authorship SCIMAGO INSTITUTIONS RANKINGS

HIGHLIGHTS

This paper presents a survey on focused web crawlers.
This paper presents the challenges in focused crawling research.
This paper presents the highlights and hindrances of existing focused web crawlers.
This paper also presents the future scope for research in focused web crawling.

Abstract

Analogous to the spectacular growth of information-superhighway, The Internet, demands for coherent and economical crawling methods are translucent to shoot up. Consequently, many innovative techniques have been put forth for efficient crawling. Among them the significant one is focused crawlers. The focused crawlers are capable in searching web pages that are suitable for the topics defined in advance. Focused crawlers attract several search engines on the grounds of efficient filtering, reduced memory and time consumption. This paper furnishes a relevance computation based survey on web crawling. A bunch of fifty two focused crawlers from the existing literature survey is categorized to four different classes - classic focused crawler, semantic focused crawler, learning focused crawler and ontology learning focused crawler. The prerequisite and the mastery of each metric with respect to harvest rate, target recall, precision and F1-score are discussed. Future outlooks, shortcomings and strategies are also suggested.

Keywords:
Web Crawler; Focused Crawler; Semantic Crawler; Learning Crawler; Machine Learning; Ontology

Author	Algorithm	Target variables	Weighting Scheme	Seed URLs	Metrics	Harvest rate achieved after 5000 web page crawls
Seyfi et al., [¹¹11 Seyfi A, Patel A. A focused crawler combinatory link and content model based on T-Graph principles. Comput Stand Interfaces. 2016;43:1-11.,¹²12 Seyfi A, Patel A, Celestino Júnior J. Empirical evaluation of the link and content-based focused Treasure-Crawler. Comput Stand Interfaces. 2016;44:54-62.]	DDS, VSM	Full page text, anchor text, sub section heading (ISH), section heading which contains ISH, main heading, data around the link and target information	TF-IDF	14% generic seed URLs and 22% on-topic seed URLs	Recall, Harvest Rate	0.27
Yajun et al., [¹⁰10 Liu WJ, Du YJ. A novel focused crawler based on cell-like membrane computing optimization algorithm. Neurocomputing [Internet]. 2014;123:266-80. Available from: http://dx.doi.org/10.1016/j.neucom.2013.06.039 http://dx.doi.org/10.1016/j.neucom.2013.... ]	CMCOA, VSM	full page text, anchor text, title text and surrounding text of paragraphs	Evolution regular, communication regular, TF-IDF	3 Seed URLs for each topic	Harvest Rate, Average Relevance and Average Errors	0.297
Almpanidis et al., [⁸8 Almpanidis G, Kotropoulos C, Pitas I. Combining text and link analysis for focused crawling-An application for vertical search engines. Inf Syst. 2007;32(6):886-908.]	VSM and HITS	Full page text and anchor text	LSI		Precision, Recall and Harvest rate	0.21
Chen et al., [⁹9 Chen Z, Ma J, Lei J, Yuan B, Lian L, Song L. A cross-language focused crawling algorithm based on multiple relevance prediction strategies. Comput Math with Appl [Internet]. 2009;57(6):1057-72. Available from: http://dx.doi.org/10.1016/j.camwa.2008.09.021 http://dx.doi.org/10.1016/j.camwa.2008.0... ]	VSM	Full page text, anchor text, URL address and link structure	TF	3 Seed URLs for each topic	Harvest Rate, Sum of info, average running time	0.22
Mani Sekhar et al., [¹⁴14 Mani Sekhar SR, Siddesh GM, Manvi SS, Srinivasa KG. Optimized focused Web Crawler with Natural Language Processing based relevance measure in bioinformatics web sources. Cybern Inf Technol. 2019;19(2):146-58.]	VSM	Full page text and anchor text	TF-IDF		Operating time and harvest rate	0.21
Farag et al., [¹³13 Farag MMG, Lee S, Fox EA. Focused crawler for events. Int J Digit Libr. 2018;19(1):3-19.]	VSM	Topic, Date and Location	TF-IDF, Regular Expression and NER	38 Seed URLs for each topic	Precision, Recall, F1-Measure and Harvest Rate	0.26
Singh et al., [¹⁵15 Singh B, Kumar Gupta D, Mohan Singh R. Improved Architecture of Focused Crawler on the basis of Content and Link Analysis. Int J Mod Educ Comput Sci. 2017;9(11):33-40.]	VSM	Full page text and link context	TF-IDF	10 Seed URLs for each topic	Harvest Rate	0.21
Geng et al., [¹⁶16 Geng Z, Shang D, Zhu Q, Wu Q, Han Y. Research on improved focused crawler and its application in food safety public opinion analysis. 2017 Chinese Autom Congr [Internet]. 2017;2847-52. Available from: http://ieeexplore.ieee.org/document/8243261/ http://ieeexplore.ieee.org/document/8243... ]	VSM and Multifactor correlation co-efficient	Full page text and crawler theme	TF-IDF		Harvest Rate, Precision and Recall	0.22
Xu et al., [¹⁷17 Xu G, Jiang P, Ma C, Daneshmand M. A Focused Crawler Model Based on Mutation Improving Particle Swarm Optimization Algorithm. Proc - 2018 IEEE Int Conf Ind Internet, ICII 2018. 2018;(Icii):173-4.]	Particle Swarm Optimization	Full page text, anchor text, surrounding text and URL text	TF-IDF	100 Seed URLs for each topic	Harvest Rate	0.29
Rungsawang et al., [⁷7 Rungsawang A, Angkawattanawit N. Learnable topic-specific web crawler. J Netw Comput Appl. 2005;28(2):97-114.]	VSM and BHITS	Title, full page text, anchor text and link context	TF-IDF	10 Seed URLs for each topic	Harvest Rate	0.27
Kumar et al., [¹⁸18 Kumar M, Vig R. Learnable Focused Meta Crawling Through Web. Procedia Technol [Internet]. 2012;6(1994):606-11. Available from: http://dx.doi.org/10.1016/j.protcy.2012.10.073 http://dx.doi.org/10.1016/j.protcy.2012.... ]	VSM, Hub score and Authority score	Full page text and anchor text	TF-IDF	Seed URLs are generated from ODP	Harvest Rate	0.26
Goyal et al., [¹⁹19 Goyal N, Bhatia R, Kumar M. A genetic algorithm based focused web crawler for automatic webpage classification. IET Conf Publ. 2016;2016(CP739).]	Genetic algorithm	Title, full page text, anchor text, paragraph text, list text, bold text and heading text	Cosine similarity	http://www.stanford.edu/ is crawled up to depth 6.	Harvest Rate	0.26
Zhao et al. [²⁰20 Zhao F, Zhou J, Nie C, Huang H, Jin H. SmartCrawler: A two-stage crawler for efficiently harvesting deep-web interfaces. IEEE Trans Serv Comput. 2016;9(4):608-20.]	Cosine Similarity	Full page text, Context of URL, anchor text, and text around URL	TF-IDF	100 Seed URLs for each topic	Harvest Rate	0.29
Jung-ran Park et al. [²¹21 Park JR, Yang C, Tosaka Y, Ping Q, Mimouni H El. Developing an automatic crawling system for populating a digital repository of professional development resources: A pilot study. J Electron Resour Librariansh. 2016;28(2):63-72.]	Cosine similarity and HITS	Full page text and anchor text	TF-IDF	15 Seed URLs for each topic	Harvest Rate	0.26
Chen et al. [²²22 Chen X, Zhang X. HAWK: A focused crawler with content and link analysis. IEEE Int Conf E-bus Eng ICEBE'08 - Work AiR'08, EM2I'08, SOAIC'08, SOKM'08, BIMA'08, DKEEE'08. 2008;677-80.]	Cosine similarity and page rank	Full page text and anchor text	TF-IDF	Seed URLs are generated from ODP	Harvest Rate	0.29
Rawat et al., [²³23 Rawat S, Patil DR. Efficient focused crawling based on best first search. Proc 2013 3rd IEEE Int Adv Comput Conf IACC 2013. 2013;908-11.]	Cosine Similarity	Full page text and anchor text	TF-IDF		Harvest Rate	0.21
Hati et al. [²⁴24 Hati D, Sahoo B, Kumar A. Adaptive focused crawling based on link analysis. ICETC 2010 - 2010 2nd Int Conf Educ Technol Comput. 2010;4:455-60.]	Cosine Similarity	Full page text, anchor text, cohesive text and also relevance score of parent pages	TF-IDF	1 Seed URL for each topic	Harvest Rate	0.27
Mangaravite et al. [²⁵25 Mangaravite V, Tavares De Assis G, Ferreira AA. Improving the efficiency of a genre-aware approach to focused crawling based on link context. Proc - 2012 8th Lat Am Web Congr LA-WEB 2012. 2012;17-23.]	Cosine Similarity	Full page text, anchor text, title text and URL text	TF-IDF	3 Seed URL for each topic	Harvest Rate	0.27
Wei et al. [²⁶26 Zhao W, Guan Z, Cao Z, Liu Z. Mining and harvesting high quality topical resources from the web. Chinese J Electron. 2016;25(1):48-57.]	VSM, cash gain and RVM	Full page text and link context	TF-IDF	10 Seed URL for each topic	Harvest rate, precision and recall	0.34
Gupta et al. [²⁷27 Gupta S, Duhan N, Bansal P. An Approach for Focused Crawler to Harvest Digital Academic Documents in Online Digital Libraries. Int J Inf Retr Res. 2019;9(3):23-47.]	Cosine Similarity	Full page text, keyword text and the title text	TF-IDF	15-20 Seed URL for each topic	Precision and Recall

Author	Algorithm	Target variables	Ontology	Seed URLs	Metrics	Harvest rate achieved after 5000 web page crawls
Bedi et al., [³⁰30 Bedi P, Thukral A, Banati H. Focused crawling of tagged web resources using ontology. Comput Electr Eng [Internet]. 2013;39(2):613-28. Available from: http://dx.doi.org/10.1016/j.compeleceng.2012.09.009 http://dx.doi.org/10.1016/j.compeleceng.... ]	Social semantic-VSM	Full page text	Concept ontology	10 Seed URLs for each topic	Harvest Rate	0.20
Yajun et al., [³³33 Du Y, Liu W, Lv X, Peng G. An improved focused crawler based on Semantic Similarity Vector Space Model. Appl Soft Comput J [Internet]. 2015;36:392-407. Available from: http://dx.doi.org/10.1016/j.asoc.2015.07.026 http://dx.doi.org/10.1016/j.asoc.2015.07... ]	SSVSM	Full page text and anchor text	WordNet	3 Seed URLs for each topic	Harvest rate, average similarity and average error	0.29
Dong et al., [⁵5 Dong H, Hussain FK. Self-adaptive semantic focused crawler for mining services information discovery. IEEE Trans Ind Informatics. 2014;10(2):1616-26.]	Hybrid string matching	Full page text, Meta data description, and link context	WordNet	Seed URLs are generated from ODP	Harvest Rate, Precision, Recall, Harmonic Mean	0.36
Dong et al., [²⁸28 Dong H, Hussain FK. Focused crawling for automatic service discovery, annotation, and classification in industrial Digital Ecosystems. IEEE Trans Ind Electron. 2011;58(6):2106-16.]	ECBR	Full page text, Meta data description, and link context	WordNet	Seed URLs are generated from ODP	Harvest Rate, Precision, Recall, Harmonic Mean	0.34
Yang et al., [³⁴34 Yang SY. OntoPortal: An ontology-supported portal architecture with linguistically enhanced and focused crawler technologies. Expert Syst Appl [Internet]. 2009;36(6):10148-57. Available from: http://dx.doi.org/10.1016/j.eswa.2009.01.004 http://dx.doi.org/10.1016/j.eswa.2009.01... ]	VSM	Full page text	WordNet	10 Seed URLs for each topic	Precision , Recall and Harvest Rate	0.34
Yajun et al., [³¹31 Du Y, Hai Y. Semantic ranking of web pages based on formal concept analysis. J Syst Softw [Internet]. 2013;86(1):187-97. Available from: http://dx.doi.org/10.1016/j.jss.2012.07.040 http://dx.doi.org/10.1016/j.jss.2012.07.... ]	Information content similarity (ICS)	Full page text and anchor text	WordNet	3 Seed URLs for each topic	Precision , Recall and Harvest Rate	0.26
Dhanith et al., [³⁵35 Joe Dhanith PR, Surendiran B. An ontology learning based approach for focused web crawling using combined normalized pointwise mutual information and Resnik algorithm. Int J Comput Appl [Internet]. 2019;0(0):1-7. Available from: https://doi.org/1206212X.2019.1684023 https://doi.org/1206212X.2019.1684023... ]	NPMI and Resnik semantic similarity	Full page text, anchor text, title text, bold text and heading text	WordNet	10 Seed URLs for each topic	Harvest Rate	0.23
Yajun et al., [³²32 Du Y, Pen Q, Gao Z. Data & Knowledge Engineering A topic-speci fi c crawling strategy based on semantics similarity. Datak [Internet]. 2013;88:75-93. Available from: http://dx.doi.org/10.1016/j.datak.2013.09.003 http://dx.doi.org/10.1016/j.datak.2013.0... ]	Formal concept Analysis	Full page text and anchor text	WordNet	3 Seed URLs for each topic	Precision , Recall, F1-Score and Harvest Rate	0.28
Yuvarani et al., [³⁶36 Yuvarani M, Iyengar NCSN, Kannan A. LSCrawler: A framework for an enhanced focused web crawler based on link semantics. Proc - 2006 IEEE/WIC/ACM Int Conf Web Intell (WI 2006 Main Conf Proceedings), WI'06. 2007;794-7.]	distance based semantic similarity	Full page text, Link context and heading text	ARP Jena	First 10 Seed URLs generated from Google for each topic	Harvest Rate	0.26
Jalilian et al., [³⁷37 Jalilian O, Khotanlou H. A new fuzzy-based method to weigh the related concepts in semantic focused web crawlers. ICCRD2011 - 2011 3rd Int Conf Comput Res Dev. 2011;3:23-7.]	distance based semantic similarity, term frequency and fuzzy inference system	Full page text	Ontology developed using protégé	2 Seed URLs for each topic	Harvest Rate	0.29
Hegade et al., [³⁸38 Hegade P, Shilpa R, Aigal P, Pai S, Shejekar P. Crawler by Inference. 2020;108-12.]	Jaccard similarity, Lesk and Wu-Palmer semantic similarity	Full page text and anchor text	WordNet	https://soundcloud.com is the seed URL	Crawling Time

Authors	Features	Algorithms	Target Variables	Training Data set	Metrics	Harvest Rate Achieved after 5000 web page crawls
Liu et al., [³3 Batsakis S, Petrakis EGM, Milios E. Improving the performance of focused web crawlers. Data Knowl Eng [Internet]. 2009;68(10):1001-13. Available from: http://dx.doi.org/10.1016/j.datak.2009.04.002 http://dx.doi.org/10.1016/j.datak.2009.0... ,⁴⁰40 Liu H, Janssen J, Milios E. Using HMM to learn user browsing patterns for focused Web crawling. Data Knowl Eng. 2006;59(2):270-91.]	Concept Graph generated using LSI and X-means	HMM	Full page text	ODP and Yahoo Directory	Harvest Rate, Precision and Recall	0.14
Peng et al., [⁴⁵45 Peng T, Liu L. Focused crawling enhanced by CBP-SLC. Knowledge-Based Syst [Internet]. 2013;51:15-26. Available from: http://dx.doi.org/10.1016/j.knosys.2013.06.008 http://dx.doi.org/10.1016/j.knosys.2013.... ]	TFIPNDF	SVM	Full page text, anchor text, link context and content blocks	Reuters corpus, 20 Newsgroup corpus and ODP	Precision, Recall, F1-measure, Error rate, Harvest rate and target recall	0.36
Diligenti et al., [³⁹39 Diligenti M, Coetzee F, Lawrence S, Giles CL, Gori M. Focused crawling using context graphs. Proc 26th ... [Internet]. 2000;527-34. Available from: http://www.vldb.org/conf/2000/P527.pdf http://www.vldb.org/conf/2000/P527.pdf... ]	TF-IDF	NB	Full page text	Manually collected dataset for 10 topics	Harvest Rate	0.29
Pant et al., [⁴¹41 Pant G, Srinivasan P. Link contexts in classifier-guided topical crawlers. IEEE Trans Knowl Data Eng. 2006;18(1):107-22.]	TF-IDF	SVM	Full page text and link context	ODP	Harvest rate, Target recall	0.31
Houqing et al., [⁴⁶46 Lu H, Zhan D, Zhou L, He D. An Improved Focused Crawler: Using Web Page Classification and Link Priority Evaluation. Math Probl Eng. 2016;2016.]	ITFIDF	NB	Full page text and link context	Reuters corpus, 20 Newsgroup corpus and ODP	Harvest rate, Target recall	0.34
Pawar et al., [⁴⁷47 Pawar N, Rajeswari K, Joshi A. Implementation of an Efficient web crawler to search medicinal plants and relevant diseases. Proc - 2nd Int Conf Comput Commun Control Autom ICCUBEA 2016. 2017;48:87-92.]	Cosine similarity values	NB	Full page text, title text, anchor text, URL text and meta description text	Medicinal plant dataset	Precision, Recall, Accuracy and Harvest Rate	0.31
Amalia et al., [⁴⁹49 Amalia A, Gunawan D, Najwan A, Meirina F. Focused crawler for the acquisition of health articles. Proc 2016 Int Conf Data Softw Eng ICoDSE 2016. 2017;(October).]	TF-IDF	Multinomial NB	Full page text	Health and non-health dataset	Harvest Rate	0.29
Suebchua et al., [⁴⁸48 Suebchua T, Manaskasemsak B, Rungsawang A, Yamana H. History-enhanced focused website segment crawler. Int Conf Inf Netw. 2018;2018-Janua:80-5.]	TF and History feature	Multinomial NB	Full page text, link context, linkage features and recent crawl logs	ODP and Yahoo Japan directory	Harvest rate	0.34
Zheng et al., [⁵⁰50 Zheng Z, Qian D. An improved focused crawler based on text keyword extraction. Proc 2016 5th Int Conf Comput Sci Netw Technol ICCSNT 2016. 2017;386-90.]	TF-IDF	NB	Full page text, anchor text and link context	50000 technical reports with the following fields ID, title, abstract, keywords	Harvest Rate	0.27
Liu et al., [⁴²42 Liu H, Milios E. Probabilistic models for focused web crawling. Comput Intell [Internet]. 2012;28(3):289-328. Available from: http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?action=shwart&index=an&req=16352297⟨=en http://nparc.cisti-icist.nrc-cnrc.gc.ca/... ]	Cosine similarity	MEMM and CRF	edge, full page text, meta description, URL text, and anchor text	Yahoo Directory, ODP	Precision and Harvest rate	0.34
Illiou et al., [⁵¹51 Iliou C, Kalpakis G, Tsikrika T, Vrochidis S, Kompatsiaris I. Hybrid focused crawling for homemade explosives discovery on surface and dark Web. Proc - 2016 11th Int Conf Availability, Reliab Secur ARES 2016. 2016;229-34.]	TF-IDF	SVM with RBF kernel	Full page text, anchor text and link context	600 samples collected from Yahoo directory	Precision, Recall and Harvest Rate	0.31
Kaur et al. [⁵²52 Geetha G, Kaur S. Smart Focused Web Crawler for Hidden Web [Internet]. Vol. 40, Information and Communication Technology for Competitive Strategies, Lecture Notes in Networks and Systems. Springer Singapore; 2019. 419-427 p. Available from: http://link.springer.com/10.1007/978-981-13-0586-3_42 http://link.springer.com/10.1007/978-981... ]	TF-IDF	Decision Tree	Full page text	Tel-8 and common crawl datasets	-	-
Fu et al., [⁴³43 Fu T, Abbasi A, Zeng D, Chen H. Sentimental Spidering. ACM Trans Inf Syst [Internet]. 2012;30(4):1-30. Available from: http://dl.acm.org/citation.cfm?doid=2382438.2382443 http://dl.acm.org/citation.cfm?doid=2382... ]	Term Frequency	Entropy based classifier and GBS classifier	Full page text and Sentiment data	corporate social responsibility (CSR) and post-marketing drug surveillance (PMDS)	Precision, Recall, F1-score and Harvest Rate	0.34
Vural et al., [⁴⁴44 Vural AG, Cambazoglu BB, Senkul P. Sentiment-focused web crawling. ACM Trans web. 2014;8(4):22.1-22.21. https://doi.org/22.1-22.21... ]	21 features	Support Vector regression	Page URL, Anchor text and referring page	ClueWeb09-B	Accumulated sentiment score, and average page rank
Zowalla et al., [⁵³53 Zowalla R, Wetter T, Math D, Pfeifer D. Crawling the German Health Web : Exploratory Study and Graph Analysis Corresponding Author : 2020;22:1-22.]	TF-IDF	SVM	Full page text	87,562 web pages were collected from various medical sources	Harvest Rate	0.31
Dhanith et al., [⁵⁴54 Dhanith PRJ, Surendiran B, Raja SP. A Word Embedding Based Approach for Focused Web Crawling Using the Recurrent Neural Network. Int J Interact Multimed Artif Intell. 2020;In Press(In Press):1.]	A-SGNS based cosine	RNN	Full page text and anchor text	Manually collected 360,000 topic and web page pairs	Harvest Rate and Irrelevance Ratio	0.42

Author	Features	Algorithm	Target Variables	Ontology Used	Dataset Used	Metrics	Harvest Rate achieved after 5000 web page crawls
Zheng et al., [⁶6 Zheng HT, Kang BY, Kim HG. An ontology-based approach to learnable focused crawling. Inf Sci (Ny) [Internet]. 2008;178(23):4512-22. Available from: http://dx.doi.org/10.1016/j.ins.2008.07.030 http://dx.doi.org/10.1016/j.ins.2008.07.... ]	Term Frequency of relevant concepts	ANN	Full page text	UMLS	Manually collected dataset	Harvest Rate, performance-cost ratio	0.2044
Saleh et al., [⁵⁶56 Saleh AI, Abulwafa AE, Al Rahmawy MF. A web page distillation strategy for efficient focused crawling based on optimized Naïve bayes (ONB) classifier. Appl Soft Comput J [Internet]. 2017;53:181-204. Available from: http://dx.doi.org/10.1016/j.asoc.2016.12.028 http://dx.doi.org/10.1016/j.asoc.2016.12... ]	Term frequencies of the domain keywords	ONB, Genetic Algorithm and SVM	Full page text	D²O	Web Data Commons dataset	Precision, Accuracy, Error, and Harvest Rate	0.37
Dong et al., [⁵⁵55 Hussain HD and FK. SOF: a semi-supervised ontology-learning-based focused crawler. Concurr Comput Pract Exp. 2013;25(6):1755-70.]	Resnik semantic similarity and the probability based similarity	SVM	Full page text	WordNet	Manually collected dataset	Precision, Recall, Harmonic Mean, Harvest Rate	0.36
Capuano et al. [⁵⁷57 Capuano A, Rinaldi AM, Russo C. An ontology-driven multimedia focused crawler based on linked open data and deep learning techniques. Multimed Tools Appl. 2019;]	Features based on ImageNet	Hybrid semantic similarity algorithm and CNN	Full page text and images in the web page	WordNet and ImageNet	Manually collected dataset	Harvest Rate	0.31
Hassan et al. [⁵⁹59 Hassan T, Cruz C, Bertaux A. Predictive and evolutive cross-referencing for web textual sources. Proc Comput Conf 2017. 2018;2018-Janua(July):1114-22.]	TF-IDF	hierarchical multi label classification	Full page text	Ontology described knowledgebase designed using stardog	45k economic-related news	Harvest Rate and Average Similarity

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[1] *Correspondence: joe.dhanith@gmail.com; Tel.: +91-8903939076 (J.D.P.N.R.M.).