| Number | Description | File | Comment | File (En) |
| 36 |
| Veretennikov A.B. Relevance ranking for proximity full-text search based on additional indexes with multi-component keys, Vestnik Udmurtskogo Universiteta. Matematika. Mekhanika. Komp'yuternye Nauki, 2021, vol. 31, issue 1, pp. 132-148. |
| https://doi.org/10.35634/vm210110 |
The problem of proximity full-text search is considered. If a search query contains high-frequently occurring words, then multi-component key indexes deliver an improvement in the search speed compared with ordinary inverted indexes. It was shown that we can increase the search speed by up to 130 times in cases when queries consist of high-frequently occurring words. In this paper, we investigate how the multi-component key index architecture affects the quality of the search. We consider several well-known methods of relevance ranking, where these methods are of different authors. Using these methods, we perform the search in the ordinary inverted index and then in an index enhanced with multi-component key indexes. The results show that with multi-component key indexes we obtain search results that are very close, in terms of relevance ranking, to the search results that are obtained by means of ordinary inverted indexes.
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| Scopus, Web of Science, VAK 12 |
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| 35 |
| Veretennikov A.B. Selection of Optimal Parameters in the Fast K-Word Proximity Search Based on Multi-component Key Indexes. Supplementary Proceedings of the XXII International Conference on Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2020), Voronezh, Russia, October 13-16, 2020, P. 336-350 |
| http://ceur-ws.org/Vol-2790/ |
Proximity full-text search is commonly implemented in contemporary full-text search systems. Let us assume that the search query is a list of words. It is natural to consider a document as relevant if the queried words are near each other in the document. The proximity factor is even more significant for the case where the query consists of frequently occurring words. Proximity full-text search requires the storage of information for every occurrence in documents of every word that the user can search. For every occurrence of every word in a document, we employ additional indexes to store information about nearby words, that is, the words that occur in the document at distances from the given word of less than or equal to the MaxDistance parameter. We showed in previous works that these indexes can be used to improve the average query execution time by up to 130 times for queries that consist of words occurring with high-frequency. In this paper, we consider how both the search performance and the search quality depend on the value of MaxDistance and other parameters. Well-known GOV2 text collection is used in the experiments for reproducibility of the results. We propose a new index schema after the analysis of the results of the experiments.
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| CEUR, Scopus |
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| 34 |
| Veretennikov A.B. (2021) An Improved Algorithm for Fast K-Word Proximity Search Based on Multi-component Key Indexes. In: Arai K., Kapoor S., Bhatia R. (eds) Intelligent Systems and Applications. IntelliSys 2020. Advances in Intelligent Systems and Computing, vol 1251. Springer, Cham. |
| https://doi.org/10.1007/978-3-030-55187-2_37 |
A search query consists of several words. In a proximity full-text search, we want to find documents that contain these words near each other. This task requires much time when the query consists of high-frequently occurring words. If we cannot avoid this task by excluding high-frequently occurring words from consideration by declaring them as stop words, then we can optimize our solution by introducing additional indexes for faster execution. In a previous work, we discussed how to decrease the search time with multi-component key indexes. We had shown that additional indexes can be used to improve the average query execution time up to 130 times if queries consisted of high-frequently occurring words. In this paper, we present another search algorithm that overcomes some limitations of our previous algorithm and provides even more performance gain.
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| SpringerLink, Scopus |
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| 33 |
| Veretennikov A.B. (2020) Proximity Full-Text Searches of Frequently Occurring Words with a Response Time Guarantee. In: Pinelas S., Kim A., Vlasov V. (eds) Mathematical Analysis With Applications. CONCORD-90 2018. Springer Proceedings in Mathematics & Statistics, vol 318. Springer, Cham |
| https://doi.org/10.1007/978-3-030-42176-2_37 |
Full-text search engines are important tools for information retrieval. In a proximity full-text search, a document is relevant if it contains query terms near each other, especially if the query terms are frequently occurring words.
For each word in the text, we use additional indexes to store information about nearby words at distances from the given word of less than or equal to MaxDistance, which is a parameter. A search algorithm for the case when the query consists of high-frequently used words is discussed. In addition, we present results of experiments with different values of MaxDistance to evaluate the search speed dependence on the value of MaxDistance. These results show that the average time of the query execution with our indexes is 94.7-45.9 times (depending on the value of MaxDistance) less than that with standard inverted files when queries that contain high-frequently occurring words are evaluated.
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| SpringerLink, Scopus |
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| 32 |
| Veretennikov A.B. (2019) Proximity Full-Text Search by Means of Additional Indexes with Multi-component Keys: In Pursuit of Optimal Performance. In: Manolopoulos Y., Stupnikov S. (eds) Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2018. Communications in Computer and Information Science, vol 1003. Springer, Cham. |
| https://doi.org/10.1007/978-3-030-23584-0_7 |
Full-text search engines are important tools for information retrieval. In a proximity full-text search, a document is relevant if it contains query terms near each other, especially if the query terms are frequently occurring words. For each word in a text, we use additional indexes to store information about nearby words that are at distances from the given word of less than or equal to the MaxDistance parameter. We showed that additional indexes with three-component keys can be used to improve the average query execution time by up to 94.7 times if the queries consist of high-frequency occurring words. In this paper, we present a new search algorithm with even more performance gains. We consider several strategies for selecting multi-component key indexes for a specific query and compare these strategies with the optimal strategy. We also present the results of search experiments, which show that three-component key indexes enable much faster searches in comparison with two-component key indexes.
This is a pre-print of a contribution “Veretennikov A.B. (2019) Proximity Full-Text Search by Means of Additional Indexes with Multi-component Keys: In Pursuit of Optimal Performance.” published in “Manolopoulos Y., Stupnikov S. (eds) Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2018. Communications in Computer and Information Science, vol 1003” published by Springer, Cham. This book constitutes the refereed proceedings of the 20th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2018, held in Moscow, Russia, in October 2018. The 9 revised full papers presented together with three invited papers were carefully reviewed and selected from 54 submissions. The final authenticated version is available online at https://doi.org/10.1007/978-3-030-23584-0_7. |
|
| SpringerLink, Scopus |
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| 31 |
| Veretennikov A.B. An efficient algorithm for three-component key index construction, Vestnik Udmurtskogo Universiteta. Matematika. Mekhanika. Komp'yuternye Nauki, 2019, vol. 29, issue 1, pp. 117-132. |
| http://vm.udsu.ru/issues/archive/issue/2019-1-11 |
Proximity full-text searches in large text arrays are considered. A search query consists of several words. The search result is a list of documents containing these words. In a modern search system, documents that contain search query words that are near each other are more relevant than other documents. To solve this task, for each word in each indexed document, we need to store a record in the index. In this case, the query search time is proportional to the number of occurrences of the queried words in the indexed documents. Consequently, it is common for search systems to evaluate queries that contain frequently occurring words much more slowly than queries that contain less frequently occurring, ordinary words. For each word in the text, we use additional indexes to store information about nearby words at distances from the given word of less than or equal to MaxDistance, which is a parameter. This parameter can take a value of 5, 7, or even more. Three-component key indexes can be created for faster query execution. Previously, we presented the results of experiments showing that, when queries contain very frequently occurring words, the average time of the query execution with three-component key indexes is 94.7 times less than that required when using ordinary inverted indexes. In the current work, we describe a new three-component key index building algorithm. We prove the correctness of the algorithm. We present the results of experiments of the index creation in dependence of the value of MaxDistance.
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| Scopus, Web of Science, VAK 11 |
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| 30 |
| Veretennikov A.B. Proximity full-text search with a response time guarantee by means of additional indexes with multi-component keys. Selected Papers of the XX International Conference on Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2018), Moscow, Russia, October 9-12 2018, 123-130 (2018) |
| http://ceur-ws.org/Vol-2277 |
Full-text search engines are important tools for information retrieval. In a proximity full-text search, a document is relevant if it contains query terms near each other, especially if the query terms are frequently occurring words. For each word in the text, we use additional indexes to store information about nearby words at distances from the given word of less than or equal to MaxDistance, which is a parameter. We had shown that additional indexes with three-component keys can be used to improve the average query execution time up to 94.7 times if the queries consist of high-frequency used words. In this paper, we present a new search algorithm with even more performance gains. We also present results of search experiments, which show that three-component key indexes enable much faster searches in comparison with two-component key indexes.
This is a pre-print of a contribution “Veretennikov A.B. Proximity full-text search with a response time guarantee by means of additional indexes with multi-component keys” published in “Selected Papers of the XX International Conference on Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2018), Moscow, Russia, October 9-12 2018, 123-130 (2018)” published by CEUR. The final authenticated version is available online at: http://ceur-ws.org/Vol-2277. |
|
| CEUR, Scopus |
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| 29 |
| Veretennikov A.B. (2019) Proximity Full-Text Search with a Response Time Guarantee by Means of Additional Indexes. In: Arai K., Kapoor S., Bhatia R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 868, pp 936-954. Springer, Cham |
| https://doi.org/10.1007/978-3-030-01054-6_66 |
Full-text search engines are important tools for information retrieval. Term proximity is an important factor in relevance score measurement. In a proximity full-text search, we assume that a relevant document contains query terms near each other, especially if the query terms are frequently occurring words. A methodology for high-performance full-text query execution is discussed. We build additional indexes to achieve better efficiency. For a word that occurs in the text, we include in the indexes some information about nearby words. What types of additional indexes do we use? How do we use them? These questions are discussed in this work. We present the results of experiments showing that the average time of search query execution is 44-45 times less than that required when using ordinary inverted indexes.
This is a pre-print of a contribution “Veretennikov A.B. Proximity Full-Text Search with a Response Time Guarantee by Means of Additional Indexes” published in “Arai K., Kapoor S., Bhatia R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 868” published by Springer, Cham. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-01054-6_66. The work was supported by Act 211 Government of the Russian Federation, contract № 02.A03.21.0006. |
|
| SpringerLink, Scopus |
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| 28 |
| Veretennikov A. B. Proximity full-text search with response time guarantee by means of three component keys // Bulletin of the South Ural State University. Series: Computational Mathematics and Software Engineering. 2018. vol. 7, no. 1. pp. 60–77. (in Russian) |
| http://dx.doi.org/10.14529/cmse180105 |
Searches for phrases and word sets in large text arrays by means of additional indexes are considered. A search result is a list of documents that contain specified words. A document which contains the query words near each other is more important. Such a tack required to store one posting per any word occurrence in a document. Some search systems use a list of stop words and exclude any information about a stop word from the index thus reducing search quality. In our paper we store information about all words to ensure search quality and build additional indexes for most frequently used words. Use of the additional indexes may reduce the query processing time by an order of magnitude and more in comparison with standard indexes. A new three component key based index has described. Results of search experiments are given and new search algorithm is provided. The results of the experiments shows 90 times improvement of search time for a class of queries containing most frequently used words in comparison with default inverted file.
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| VAK 10 |
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| 27 |
| Veretennikov A. B. Efficient full-text proximity search by means of three component keys // Control systems and information technologies, 2017, no. 3(69), pp. 25–32, In Russian |
Searches for phrases and word sets in large text arrays by means of additional indexes are considered. Their use may reduce the query processing time by an order of magnitude in comparison with standard indexes. A new three compo-nent key based index has described. Results of experiments are given.
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clb8.pdf
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2017-09
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214 481 bytes (0,20 MB)
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Ru
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| VAK 9 |
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| 26 |
| Alexander B. Veretennikov. About a structure of easily updatable full-text indexes). Proceedings of the 48th International Youth School-Conference ''Modern Problems in Mathematics and its Applications''. P. 30-41 |
| http://ceur-ws.org/Vol-1894/ |
We consider strategies of organization easy updatable associative arrays in the external memory. These arrays are used for full-text search. We study indexes with different keys: single word form, two word forms, sequence of word forms. Structure of storage depends on the size of key's data. Results of the experiments are given in the context of the proximity full-text search by means of additional indexes.
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alg4.pdf
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2017-09
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522 112 bytes (0,50 MB)
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Ru
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| CEUR, Scopus |
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| 25 |
| Vyacheslav E. Kopeytsev, Alexander B. Veretennikov. On the analysis of application algorithms using drivers in Windows 7-10
operating systems. Proceedings of the 48th International Youth School-Conference ''Modern Problems in Mathematics and its Applications''. P. 8-19 |
| http://ceur-ws.org/Vol-1894/ |
This article about creation of system for application monitoring using Windows Driver Foundation. It describes tracing of operations with file system, network and registry, that can help to solve a wide range of tasks, from testing and analysis of input-output models to malware analysis. The document describes the architecture of this system, the methods used to solve the tasks. Also, given examples of problems, including those not previously described, as well as their solutions, some of which have been modified and improved for application in this task.
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alg2.pdf
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2017-09
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458 291 bytes (0,44 MB)
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Ru
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| CEUR, Scopus |
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| 24 |
| Veretennikov A.B. Effektivnyi polnotekstovyi poisk s ispol'zovaniem dopolnitel'nykh indeksov chasto vstrechayushchikhsya slov [Efficient Full-Text Search by Means of Additional Indexes of Frequently Used Words] Sistemy upravleniya i informatsionnye tekhnologii [Control Systems and Information Technologies]. 2016. vol. 66, no. 4. pp. 52-60, In Russian. |
Searches for phrases and word sets in large text arrays by means of additional indexes are considered. Their use may reduce the query processing time by an order of magnitude in comparison with standard indexes. Several search strategies described. Results of experiments are given.
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clb7.pdf
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2016-12
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226 456 bytes (0,22 MB)
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Ru
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| VAK 8 |
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| 23 |
| Veretennikov A. B. O primenenii dopolnitel'nykh indeksov chasto vstrechayushchikhsya slov dlya polnotekstovogo poiska [Using additional indexes frequently used words for full-text search] // Analitika i upravlenie dannymi v oblastyakh s intensivnym ispol'zovaniem dannykh. XVIII Mezhdunarodnaya konferentsiya DAMDID / RCDL’2016 [Data Analytics and Management In Data Intensive Domains XVIII International Conference DAMDID / RCDL’2016]. 2016. pp. 217-224, In Russian |
Different words can occur in texts with different frequency. We describe additional indexes, intended for speeding up search in case the search query contains frequently used words. We defined several groups of words and developed different methods for each group. Index writing optimization is given. In case of search query is a set of frequently used words a search algorithm explained.
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| 22 |
| Veretennikov A.B. Sozdanie dopolnitel'nykh indeksov dlya bolee bystrogo polnotekstovogo poiska fraz, vklyuchayushchikh chasto vstrechayushchiesya slova [Creating additional indexes for fast full-text searching phrases that contains frequently used words] // Sistemy upravleniya i informatsionnye tekhnologii [Control systems and information technologies]. 2016. no. 1(63), pp. 27-33, In Russian. |
The problems of searching phrases in the large text arrays are considered and solved using additional indexes. With additional indexes we can perform search query more than ten times faster than with standard inverted files. Algorithms for creating additional indexes for frequently used words are described.
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clb6.pdf
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2016-02
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211 730 bytes (0,20 MB)
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Ru
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| VAK 7 |
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| 21 |
| Веретенников А.Б. Создание многопанельных интерфейсов программ на скриптовых языках // Вестник компьютерных и информационных технологий. 2016. № 2 (140). С. 28-33. |
Scripting languages such as JavaScript are proven to be the effective way to build Web interfaces, but have limited features to build interfaces of Desktop applications. But a method to create complex user interfaces of the Desktop applications exists. For example we are considering the dockable windows interface. A user interface usually consists of some panels. The docking framework provides a way to change layout. The user can move panels by using drag and drop from one place to another and can change size of the panels. Dockable windows are used in the Microsoft Visual Studio and Eclipse. In this paper a docking framework for scripting languages, its model and API are presented. The goal is to develop as simple and concise API as possible. An implementation of the model is provided. Model itself is not dependent on the implementation. Building user interface using scripting languages have advantages described in the paper. Scripting languages are often referred to as glue languages or ever system integration languages. They are intended for connecting components developed with other languages. With scripting languages the system business logic can be isolated from the user interface. The user interface can be rapidly developed, supported and updated.
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| VAK 6 |
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| 20 |
| Veretennikov A. B. Ispol'zovanie dopolnitel'nykh indeksov dlya bolee bystrogo polnotekstovogo poiska fraz, vklyuchayushchikh chasto vstrechayushchiesya slova [Using Additional Indexes for Fast Full-Text Searching Phrases that Contains Frequently Used Words] Sistemy upravleniya i informatsionnye tekhnologii [Control Systems and Information Technologies]. 2013. vol. 52, no. 2. pp. 61-66, In Russian. |
The problems of searching phrases in the large text arrays are considered and solved using additional indexes. With additional indexes we can perform search query more than ten times faster than with standard inverted files.
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clb5.pdf
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2013-06
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132 148 bytes (0,13 MB)
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Ru
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| VAK 5 |
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| 19 |
| Veretennikov A.B. O poiske fraz i naborov slov v polnotekstovom indekse [Searching for phrases and word sets in a full-text index], Sistemy upravleniya i informatsionnye tekhnologii [Control systems and information technologies], 2012, no. 2.1(48), pp. 125–130, in Russian. |
The problems of searching phrases in the large text arrays are considered and solved using additional indexes.
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clb4.pdf
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2012-03
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140 516 bytes (0,13 MB)
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Ru
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| VAK 4 |
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| 18 |
| Veretennikov A. B. Ob optimizatsii poiska fraz i naborov slov v polnotekstovom indekse [Optimizing the search for phrases and word sets in a full-text index], Sovremennye problemy matematiki. Tezisy Mezhdunarodnoi (43-i Vserossiiskoi) molodezhnoi shkoly-konferentsii [Current Mathematical Problems: Abstracts of the Proceedings of the 43th International Russian Young Scientists’ Conference), Yekaterinburg, 2012, pp. 203–205, In Russian. |
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| 17 |
| Veretennikov A. B. Polnotekstovyi indeks dlya chasto obnovlyayushchikhsya bibliotek [Full-text index for frequently updated libraries], Trudy 13-i Vserossiiskoi nauchnoi konferentsii «Elektronnye biblioteki: perspektivnye metody i tekhnologii, elektronnye kollektsii» - RCDL'2011 [Proceedings of RCDL 2011: Thirteenth Russian Scientific Conference on Electronic Libraries: Promising Methods and Technologies, Electronic Collections], Voronezh: Izd. Poligr. Tsentr VGU, 2011, pp. 157–163, In Russian. |
Author introduce a new data structure for fast indexing of large volumes of texts and a software system based on this structure. The latter is more effective for inserting data into indexes than other known data structures, and is comparable with them in the data retrieval. An new approach for inserting small amount of new data given.
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| 16 |
| Веретенников А.Б. Метод организации индекса коллекции XML документов. Современные проблемы математики: тезисы 42-й Всероссийской молодежной школы-конференции. Екатеринбург: Институт математики и механики УрО РАН, 2011. |
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| 15 |
| Veretennikov A. B. Theoretical research of the performance of CLB-Trees // Control Systems and Information Technologies. 2010. vol. 42, no. 4.1. pp. 123-128, In Russian. |
The problems of search in the large text arrays are considered and solved using the new data structure proposed earlier by author, CLB-Tree. Theoretical estimations of efficiency and proofs are given.
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clb3.pdf
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2011-01-10
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127 770 bytes (0,12 MB)
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Ru
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| VAK 3 |
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| 14 |
| Веретенников А. Б. О платформе для электронной текстовой библиотеки.
Материалы конференции «Математическое моделирование, численные методы и комплексы программ». Екатеринбург: Изд-во Урал. Ун-та, 2010. с. 30-34. |
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KVM.pdf
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2010-06-12
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79 100 bytes (0,08 MB)
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Веретенников А. Б. О методе оптимизации создания CLB-дерева.
Проблемы теоретической и прикладной математики: Тезисы 41-й Всероссийской молодежной конференции. Екатеринбург: УрО РАН, 2010. с. 429-435. |
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Веретенников А. Б. Программный комплекс и эффективные методы организации и индексации больших массивов текстов.
Автореферат диссертации на соискание ученой степени кандидата физико-математических наук. |
| http://hdl.handle.net/10995/2338 |
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| 11 |
| Veretennikov A. B. Programmnyi kompleks i effektivnye metody organizatsii i indeksatsii bol'shikh massivov tekstov [Software and Effective Methods for Organizing and Indexing Large Text Collections], Cand. Sci. Dissertation, Yekaterinburg, 2009. (In Russian). |
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diss.pdf
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2009-12-11
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797 876 bytes (0,76 MB)
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| Веретенников А. Б. Размышление об использовании Treap при работе с неравномерно распределенными данными.
Материалы межвузовской научной конференции по проблемам информатики «СПИСОК 2009». Екатеринбург. 2009. с. 14-18 |
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Веретенников А. Б. Сравнение эффективности CLB-дерева в 32-битных и 64-битных архитектурах.
Материалы межвузовской научной конференции по проблемам информатики «СПИСОК 2009». Екатеринбург. 2009. с. 7-13.
(http://spisok.usu.ru/). |
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| Веретенников А. Б. Гибкий подход к проблеме поиска похожих документов.
Проблемы теоретической и прикладной математики: Труды 40-й Всероссийской молодежной конференции. Екатеринбург: УрО РАН, 2009. с. 392-396. |
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| Veretennikov A.B. Effektivnaya indeksatsiya tekstovykh dokumentov s ispol'zovaniem CLB-derev'ev [Effective indexing of text documents by means of CLB trees], Sistemy upravleniya i informatsionnye tekhnologii [Control systems and information technologies], 2009, no. 1.1(35), pp. 134–139, In Russian |
The problems of search in the large text arrays are considered and solved us-ing the new data structure proposed earlier by author, CLB-Tree. Theoretical estimations of efficiency and results of computer experiments are given.
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clb2.rtf
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2008-10-31
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251 212 bytes (0,24 MB)
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| Веретенников А. Б. Библиотека для создания оконных интерфейсов на любых скриптовых языках
в операционной системе Windows. Информационно-математические технологии в экономике, технике и образовании:
Тезисы докладов Третьей международной научной конференции. Екатеринбург: УГТУ-УПИ, 2008. с. 220-221. |
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Веретенников А. Б. Новый подход к быстрому выделению памяти в программах на C++.
Проблемы теоретической и прикладной математики: Труды 37-й Региональной молодежной конференции.
Екатеринбург: УрО РАН, 2006, с. 413-417.
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| Veretennikov, A.B. Sozdanie legko obnovlyaemykh tekstovykh indeksov [Creation of text indexes that are easy to update], Elektronnye biblioteki: perspektivnye metody i tekhnologii, elektronnye kollektsii: Trudy Desyatoi Vserossiiskoi nauchnoi konferentsii «RCDL'2008» [Proceedings of RCDL 2008: Tenth Russian Scientific Conference on Electronic Libraries: Promising Methods and Technologies, Electronic Collections], Dubna, 2008, pp. 149–154. |
Author introduce a new data structure for fast indexing of large volumes of texts and a software system based on this structure. The latter is more effective for inserting data into indexes than other known data structures, and is comparable with them in the data retrieval.
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Веретенников А. Б. Эффективное создание текстовых индексов.
Проблемы теоретической и прикладной математики: Труды 39-й Всероссийской молодежной конференции. Екатеринбург: УрО РАН, 2008. с. 348-350.
(http://kungurka.imm.uran.ru/). |
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