Queries for search engines (such as google) contains some information about the intent and interest of the user, which can be used for user profiling, recommendation etc. As far as I know, there are already lots of methods to deal with relatively long texts, such as news, articles, essays, and extract useful features from them. However, queries are usually too short and may related to many different areas, I wonder if there are some advanced methods (not simple word embedding) already verified to be effective in extracting information from query texts? Thanks !!!
I have used Word Mover's Distance with pretty good results in the past for computing similarity of short texts . Here is the paper describing it http://proceedings.mlr.press/v37/kusnerb15.pdf and there are multiple Python and R packages implementing it (I used text2vec).
Can somebody recommend me a data mining in Management Information Systems research topic
Can be here anything worthwhile will find?
References to the work of Professor E. V. Lutsenko at the ASK-analysis of texts
Ask-the analysis of the texts allows:
- form generalized linguistic images of classes (semantic cores) based on fragments or examples of related texts in any language;'
- quantitatively compare the linguistic image of a particular person or description of an object or process with the generalized linguistic images of groups (classes);
- compare generalized linguistic images of classes with each other and create their clusters and constructs;
- to investigate the simulated subject area by studying its linguistic system-cognitive model;
- to carry out intellectual attribution of texts, i.e. to determine the probable authorship of anonymous and pseudonymous texts, Dating, genre and semantic orientation of the content of texts;
- all this can be done for any natural or artificial language or coding system.
Lutsenko E. V. Synthesis of semantic cores of scientific specialties of the higher attestation Commission of the Russian Federation and automatic classification of articles on scientific specialties with the use of ask-analysis and intellectual system "Eidos" (on the example Of the scientific journal of Kubgau and its scientific specialties: mechanization, agronomy and veterinary medicine) / E. V. Lutsenko, N. V. Andrafanova, N. V. Potapova / / Polythematic network electronic scientific journal of the Kuban state agrarian University (Scientific journal of Kubgau) [Electronic resource]. - Krasnodar: Kubgau, 2019. - No. 01(145). Pp. 31-102. – IDA [article ID]: 1451901033. - Access mode: http://ej.kubagro.ru/2019/01/pdf/33.pdf, 4.5 C. p. l.
Lutsenko E. V. Formation of the semantic core of veterinary medicine by Automated system-cognitive analysis of passports of scientific specialties of the HAC of the Russian Federation and automatic classification of texts in the areas of science / E. V. Lutsenko / / Polytematic network electronic scientific journal of the Kuban state agrarian University (Scientific journal of Kubgau) [Electronic resource]. - Krasnodar: Kubgau, 2018. - No. 10(144). P. 44 – 102. – IDA [article ID]: 1441810033. - Access mode: http://ej.kubagro.ru/2018/10/pdf/33.pdf, 3,688 C. p. l.
Lutsenko E. V. Intellectual binding of incorrect references to literary sources in bibliographic databases with the use of ask-analysis and the "Eidos" system (on the example of the Russian scientific citation index-RSCI) / E. V. Lutsenko, V. A. Glukhov / / Polythematic network electronic scientific journal of the Kuban state agrarian University (scientific journal of Kubgau) [Electronic resource]. - Krasnodar: Kubgau, 2017. - No. 01 (125). C. 1 – 65. – IDA [article ID]: 1251701001. - Access mode: http://ej.kubagro.ru/2017/01/pdf/01.pdf, 4,062 C. p. l.
Lutsenko E. V. Application of ask-analysis and intellectual system "Eidos" for the solution in General form of the problem of identification of literary sources and authors by standard, non-standard and incorrect bibliographic descriptions / E. V. Lutsenko / / Polytematic network electronic scientific journal of the Kuban state agrarian University (scientific journal of Kubgau) [Electronic resource]. - Krasnodar: Kubgau, 2014. - No. 09 (103). S. 498 – 544. – IDA [article ID]: 1031409032. - Access mode: http://ej.kubagro.ru/2014/09/pdf/32.pdf, 2,938 C. p. l.
Lutsenko E. V. ask-analysis of the problems of articles Of the scientific journal Kubgau in dynamics / E. V. Lutsenko, V. I. Loiko / / Politematic network electronic scientific journal of the Kuban state agrarian University (Scientific journal of Kubgau) [Electronic resource]. - Krasnodar: Kubgau, 2014. - No. 06 (100). P. 109 – 145. – IDA [article ID]: 1001406007. - Access mode: http://ej.kubagro.ru/2014/06/pdf/07.pdf, 2,312 u. p. l.
Lutsenko E. V. Attribution of anonymous and pseudonymous texts in system-cognitive analysis / E. V. Lutsenko / / Politematic network electronic scientific journal of Kuban state agrarian University (Scientific journal of kubgau) [Electronic resource]. - Krasnodar: Kubgau, 2004. - No. 03 (005). Pp. 44 – 64. – IDA [article ID]: 0050403003. - Access mode: http://ej.kubagro.ru/2004/03/pdf/03.pdf, 1,312 C. p. l.
Lutsenko E. V. Attribution of texts as a generalized problem of identification and forecasting / E. V. Lutsenko / / Politematic network electronic scientific journal of Kuban state agrarian University (Scientific journal of kubgau) [Electronic resource]. - Krasnodar: Kubgau, 2003. - No. 02 (002). P. 146 – 164. – IDA [article ID]: 0020302013. - Access mode: http://ej.kubagro.ru/2003/02/pdf/13.pdf, 1,188 C. p. l.
Lutsenko E. V., Grushevsky S. M., Grushevskaya T. M. Intellectual attribution of literary texts (text Dating, authorship and genre definition on the example Of Russian literature of the XIX and XX centuries) / ResearchGate, 2020, DOI: 10.13140/RG.2.2.27935.92324,
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