Singapore City, Singapore
Submission Deadline: Friday 12 Aug 2022
Conference Dates: Feb 27, 2023 - Mar 03, 2023
Web Search and Data Mining investigates areas of study like Information retrieval, Artificial intelligence, Machine learning, World Wide Web and Data mining. Ranking (information retrieval), Search engine, Relevance (information retrieval), Web search query and Web query classification are some of the study areas of Information retrieval discussed. The event focuses on Web query classification as well as the interrelated topic of Query expansion.
It addresses concerns in Query expansion which are intertwined with other disciplines, such as Query language, Sargable and Query optimization. The concepts on Artificial intelligence presented in it can also apply to other research fields, including Recommender system, Set (abstract data type) and Natural language processing. The main emphasis of Web Search and Data Mining is the subject of Recommender system, focusing on Collaborative filtering.
It explores issues in Machine learning which can be linked to other research areas like Context (language use) and Inference. The conference connects the study in World Wide Web with the closely related area of Data science. Data mining and Scalability are closely related fields of research discussed in Web Search and Data Mining.
The conference publications mainly tackle studies in Information retrieval, Artificial intelligence, Machine learning, World Wide Web and Data mining. Social network, Recommender system and Natural language processing are some topics wherein Artificial intelligence research discussed in the most cited publications has an impact. The works on Machine learning tackled in the conference papers bring together disciplines like Context (language use) and Inference.
Web Search and Data Mining focuses on Artificial intelligence, Machine learning, Recommender system, Information retrieval and Theoretical computer science. Context (language use), Graph (abstract data type) and Set (abstract data type) are some topics wherein Artificial intelligence research discussed in the event have an impact. Web Search and Data Mining addresses concerns in the field of Machine learning by exploring it in line with topics in Inference which intersect with Bayesian probability subjects.
Research in Recommender system tackled falls within the umbrella of World Wide Web. The tackled World Wide Web research is interrelated with Key (cryptography) which concerns subjects like Data science. Information retrieval works presented in it have a specific focus on Search engine.
A key indicator for each conference 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 at Web Search and Data Mining (based on the number of publications) are:
The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing at Web Search and Data Mining (based on the number of publications) are:
The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.
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, 6.06% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 29.03% were posted by at least one author from the top 10 institutions publishing at the conference. Another 20.65% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 19.35% of all publications and 30.97% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference 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 conference 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 at a conference. The index includes the authors publishing at the last edition of a conference, 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.
Oct 24, 2023 - Oct 27, 2023
Singapore City, Singapore
Deadline: Thursday 27 Apr 2023
Feb 28, 2022 - Feb 28, 2022
Phoenix, AZ, United States
16th ACM International Web Search and Data Mining Conference
Thank you for information!