1386-4564
Published by: Springer
http://www.springer.com/computer+science/database+management+%26+information+retrieval/journal/10791
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 496 | 32 | 33 | 12 |
The scientific interests tackled in the journal are Information retrieval, Pattern recognition (psychology), Artificial intelligence, Data mining and Relevance (information retrieval). The journal links adjacent topics like Information retrieval with World Wide Web. Information Retrieval facilitates discussions on Pattern recognition (psychology) that incorporate concepts from other fields like Context (language use), Search engine, Task (project management), Set (abstract data type) and Search engine indexing.
While Artificial intelligence is the focus of the journal, it also provided insights into the studies of Machine learning, Pattern recognition and Natural language processing. Information Retrieval features Natural language processing research that overlaps with concepts in Multilingualism. The study on Data mining presented in it intersects with the topics under Cluster analysis.
Some problems in Relevance (information retrieval) that were presented in it overlapped with concepts under Document retrieval and Relevance feedback. While work presented in Information Retrieval provided substantial information on Query expansion, it also covered topics in Query language and Query optimization. In the journal, researchers investigate the Web query classification study as part of research in the field of Web search query.
The journal publications facilitate discussions on Information retrieval, Pattern recognition (psychology), Artificial intelligence, Data mining and Machine learning. The most cited articles focus on Information retrieval but sometimes tackle the closely related topic of Rank (computer programming) which is concerned with Text retrieval. While the most cited publications focused on Artificial intelligence, they were also able to explore topics like Multilingualism and Natural language processing.
The journal investigates areas of study like Artificial intelligence, Robot, Simulation, Computer vision and Robotics. The journal explores topics in Artificial intelligence which can be helpful for research in disciplines like Human–computer interaction and Pattern recognition. The Robot works featured in Information Retrieval incorporate elements from Software and Sensor fusion.
The presented Simulation research focuses mostly on Motion planning and, on occasion, topics in DUAL (cognitive architecture), Robotic arm and Mobile manipulator. The close relationship between Data set and Global Positioning System, Robustness (computer science) and Lidar is one of the points of interest dissected in Computer vision research. Topics in Robotics were tackled in line with various other fields like Test (assessment), Visual feedback and Data science.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Information Retrieval (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Information Retrieval (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 98.36% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 0.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 100.00% of all publications and 0.00% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Another important aspect to consider is the contributions of various teaching institutions in the field of Information Retrieval and related research areas. Notably, there are numerous universities and colleges in Virginia that offer highly recognized programs for aspiring teachers who are keen to advance their knowledge and skills in these areas. Some of these programs are notably affordable and align with the state's credentialing requirements.
If you are considering to get a teaching credential in Virginia, a comprehensive guide on the best teaching credential programs in Virginia can significantly assist your decision-making process. These programs not only prepare individuals for the rigors of the classroom environment but also equip them with the necessary skills to contribute significantly to research in Information Retrieval and related disciplines.
A number of graduates from these programs have gone on to publish their research in esteemed journals such as Information Retrieval. They are making valuable contributions to topics such as Artificial Intelligence, Data mining, Machine learning, Multilingualism, and Natural language processing, among others. These institutions therefore continue to play an essential role in facilitating high-quality research in Information Retrieval and related areas.
Rocío Cañamares;Pablo Castells;Alistair Moffat
(2020)Fabrizio Sebastiani
(2020)Daniel Valcarce;Alejandro Bellogín;Javier Parapar;Pablo Castells
(2020)Haotian Zhang;Gordon V. Cormack;Maura R. Grossman;Mark D. Smucker
(2020)Juan Li;Zhicheng Dou;Yutao Zhu;Xiaochen Zuo
(2020)Yang Gao;Yang Gao;Christian M. Meyer;Iryna Gurevych
(2020)Mohamed Trabelsi;Zhiyu Chen;Brian D. Davison;Jeff Heflin
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