This paper aims to analyze patterns and characteristics of information seeking behavior in a Mobile Music Information Retrieval System, and based on this, aims to build a model for music information seeking behavior. The ultimate goal of mobile music ...
This paper aims to analyze patterns and characteristics of information seeking behavior in a Mobile Music Information Retrieval System, and based on this, aims to build a model for music information seeking behavior. The ultimate goal of mobile music information search, which is to download the music on a PC Web environment and move the files to a hardware device, has been affected by changes in the media environment, Downloading without playback and searching musical information in real-time through mobile devices is changing the environment and it is no longer limited to the location and time desired. The user is evolving, and a variety of personal services and SNS allow users to add comments and evaluate music. The purpose of sharing and communication is to take advantage of this. This paper models music information searching elements and explores how to find elements, features, and music information through the music information retrieval technology of users. In addition, the concept and field of information seeking behavior, steps of information seeking behavior, information seeking behavior from a mobile phone, the mobile phone as an information search tool, and information search factors, were compared to analyze music information search and to model information search frequency.
The causes of the information seeking behavior in the Mobile music information retrieval system include environmental factors, social factors, and psychological factors. The first category includes travel time, location and weather. Environmental factors include the season, television programs, movies, and travel. Social factors include SNS and acquaintance recommendations. The final category includes feelings, emotions, memory, and psychological factors associated with memories. Moreover, the factors that influence the selection of the search system, such as portability and mobility, accessibility of music information, the characteristics of the user to utilize music service, the user’s preferred mode of information search, data capacity, and economic factors such as cost, were found to influence sharing among a community and acquaintances. Mobile music information search methods and interventions are factors that promote and hinder music information search. The characteristics of mobile devices, data quality, economic factors, the surrounding environment and situations, language, and the amount of information derived also have an effect. There are also the factors of copyright and advertising when performing music searches on personal mobile phones.
Moreover, the participant observation studies analyze the pursuit of user information and analyzes the music information seeking behavior to construct a pattern analysis and model. The music information seeking behavior is divided into two categories, which are daily searches and searches of specific music information. In daily searches of music, users enter the search keyword, rather than rank or genre given by the music service. Information seeking centers on the recommendation list, which is generally information that flows in one direction. Instead of particular music information, which is mainly metadata such as the singer’s name or song title, a single service can show the difference among patterns of searching by inputting a part of the lyrics to direct the search box, using a plurality of services such as music information and video preview display, and verify when it is possible to reach the favored music information.
Based on the results of research, the following conclusions are given in regards to information seeking behavior on mobile music information retrieval systems. First, the user, according to various contexts, was found to be more active performing search activities on mobile devices rather than the existing music information systems on PC’s. Secondly, it was found that the ability of users to store sound files has changed the attitude towards watching with video. Third, today's music information seeking behavior satisfies the user's sensibility and sharing with other people allows the role of communication to be considered. Fourth, mobile music information seeking behavior has been investigated and is significant, provided that Web Services can be transferred to mobile devices. This reflects the current state of service extensions. Finally, when searching for music information from a PC, it is necessary to provide a broad context. Personalized mobile music service situations are performed only on mobile devices. In order to support various music information seeking behaviors among users so they can easily use the vast musical data available, they must be provided with a classification system that reflects the user's information needs.