Evaluating the retrieval effectiveness of search engines using Persian navigational queries

Mahmoudi, Maryam Tayefeh; Badie, Reza; Zahedi, Mohammad Sadegh; Azimzadeh, Masoumeh

doi:10.1109/istel.2014.7000767

Cited by 9 publications

(12 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In their study, Mahmoudi et al (2014) reported that Parsijoo's effectiveness was more than Google's, which contradicted the results of this study. Most likely, this result seems to be due to the fact that in their study, only the navigational queries were searched for, while in the present study, the queries were not limited by the topic or type.…”

Section: Discussioncontrasting

confidence: 90%

See 1 more Smart Citation

Evaluating the effectiveness of Google, Parsijoo, Rismoon, and Yooz to retrieve Persian documents

Tazehkandi

Nowkarizi

2020

LHT

View full text Add to dashboard Cite

PurposeThe purpose was to evaluate the effectiveness of Google (as an international search engine) as well as of Parsijoo, Rismoon, and Yooz (as Persian search engines).Design/methodology/approachIn this research, Google search engine as an international search engine, and three local ones, Parsijoo, Rismoon, and Yooz, were selected for evaluation. Likewise, 32 subject headings were selected from the Persian Subject Headings List, and then simulated work tasks were assigned based on them. A total of 192 students from Ferdowsi University of Mashhad were asked to search for the information needed for simulated work tasks in the selected search engines, and then to copy the relevant website URLs in the search form.FindingsThe findings indicated that Google, Parsijoo, Rismoon, and Yooz had a significant difference in the precision, recall, and normalized discounted cumulative gain. There was also a significant difference in the effectiveness (average of precision, recall, and NDCG) of these four search engines in the retrieval of the Persian resources.Practical implicationsUsers using an efficient search engine will attain more relevant documents, and Google search engine was more efficient in retrieving the Persian resources. It is recommended to use Google as it has a more efficient search.Originality/valueIn this research, for the first time, Google has been compared with local Persian search engines considering the new approach (simulated work tasks).

show abstract

Section: Discussioncontrasting

confidence: 90%

“…Mahmoudi et al (2014) evaluated the performance of Google as a well-known search engine, and that of Parsijoo as a Persian search engine by investigating how the search engines behaved for the Persian queries. They posed 2000 queries to three search engines supporting the Persian language.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the effectiveness of Google, Parsijoo, Rismoon, and Yooz to retrieve Persian documents

Tazehkandi

Nowkarizi

2020

LHT

View full text Add to dashboard Cite

show abstract

“…So the need for parsing the ODP directory, having access to logs of multiple search engines, and detection of navigational queries all are requirements of this approach. The similar research activity is the paper in [4] that is tailored for Persian documents and in it Iran.ir portal which contains 17000 Iranian sites which are categorized in different topics, are used.…”

Section: Methods Based On Known Items Searchmentioning

confidence: 99%

A review on web search engines' automatic evaluation methods and how to select the evaluation method

Azimzadeh

Badie

Esnaashari

2016

2016 Second International Conference on Web Research (ICWR)

Self Cite

View full text Add to dashboard Cite

Nowadays search engines are recognized as the pathway for accessing the tremendous amount of information in the internet. They provide aids and services for solving users' different information needs. Thus, being able to evaluate their effectiveness and performance is constantly gaining importance because these evaluations are useful for both developers and users of search engines. Developers can use the evaluation results for improving their strategies and paradigms in the development of search engines. Users, on the other hand, can identify the best performing search engines and in a better, quicker and more accurate way, gratify their information needs. Evaluation of search engines can be done in two different ways; either manually using human arbitrators or automatically using automatic machinery approaches which do not use human arbitrators and their judgments. In the case of manual evaluation methods, by now numerous and standard activities had been carried out by organizers and participants of conferences like TREC or CLEF. In the case of automatic evaluation methods, unlike variety of efforts which had been done by different researchers, no categorization and organization of such methods exists so far. As a result, anyone that wants to use one of the automatic evaluation methods must read all the relevant literature of these methods which is very time consuming and confusing activity. In this paper, we have reviewed almost all the important reported automatic methods for evaluation of search engines. Analyzing the results of this review, we have stated the requirements and prerequisites of using any of these methods. At the end, a framework for selecting the best pertinent method for each evaluation scenario has been suggested.Instead, automatic methods of evaluation are cheaper and faster to be performed.Index Terms-Web search engine, information retrieval, automatic evaluation methods.

show abstract

“…The problem with their work is that ODP does not treat all languages equally. Mahmoudi et al [19] perform same work for the Persian language. The study in [20] is based on finding the commonness or overlapping between a query and the results given by a search engine.…”

Section: Related Workmentioning

confidence: 99%

Evaluating Retrieval Effectiveness by Sustainable Rank List

et al. 2017

View full text Add to dashboard Cite

Abstract:The Internet of Things (IoT) and Big Data are among the most popular emerging fields of computer science today. IoT devices are creating an enormous amount of data daily on a different scale; hence, search engines must meet the requirements of rapid ingestion and processing followed by accurate and fast extraction. Researchers and students from the field of computer science query the search engines on these topics to reveal a wealth of IoT-related information. In this study, we evaluate the relative performance of two search engines: Bing and Yandex. This work proposes an automatic scheme that populates a sustainable optimal rank list of search results with higher precision for IoT-related topics. The proposed scheme rewrites the seed query with the help of attribute terms extracted from the page corpus. Additionally, we use newness and geo-sensitivity-based boosting and dampening of web pages for the re-ranking process. To evaluate the proposed scheme, we use an evaluation matrix based on discounted cumulative gain (DCG), normalized DCG (nDCG), and mean average precision (MAP n ). The experimental results show that the proposed scheme achieves scores of MAP@5 = 0.60, DCG 5 = 4.43, and nDCG 5 = 0.95 for general queries; DCG 5 = 4.14 and nDCG 5 = 0.93 for time-stamp queries; and DCG 5 = 4.15 and nDCG 5 = 0.96 for geographical location-based queries. These outcomes validate the usefulness of the suggested system in helping a user to access IoT-related information.

show abstract

Evaluating the retrieval effectiveness of search engines using Persian navigational queries

Cited by 9 publications

References 15 publications

Evaluating the effectiveness of Google, Parsijoo, Rismoon, and Yooz to retrieve Persian documents

Evaluating the effectiveness of Google, Parsijoo, Rismoon, and Yooz to retrieve Persian documents

A review on web search engines' automatic evaluation methods and how to select the evaluation method

Evaluating Retrieval Effectiveness by Sustainable Rank List

Contact Info

Product

Resources

About