information visualization/self-organizing map
本研究以1992到1997年間LIS的17種期刊論文為研究資源，抽取論文和作者兩種單位的共被引關係，利用MDS和SOM兩種方法，並配合叢集分析(cluster analysis)產生科學地圖(science map)。作者認為這兩種方法都運用了維度縮減(dimensionality-reduction)的效用，並且具有互補的效果，研究結果發現不管是MDS或是SOM在作者共被引所產生的科學地圖上，大多都可以將圖形上映射的作者分為科學計量學(scientometrics)、引用關係研究(citationist)、書目計量學(bibliometrics)、傳播理論(communication theory)、資訊檢索的認知研究(cognitive information retrieval)和資訊檢索的演算法研究(algorithmic information retrieval)，並且都屬於科學研究(science studies)的前三者在圖形上位置相當接近，兩種資訊檢索研究的距離也很相近。在論文共被引上，由於門檻較低，MDS和SOM的科學地圖上，除了原先的科學研究和兩種資訊檢索研究所組成的資訊科學研究以外，還包括圖書館研究與管理學兩個區域。
作者認為MDS產生的科學地圖可以保留論文(或作者)原先在高維度的距離關係，SOM則是保留了它們的型態(topology)關係。
The appearance of studies pertaining to library science reveals the relationship of this realm with information science. Especially significant is the presence of the management on the journal maps.
From a methodological standpoint, meanwhile, we would agree with those authors who consider MDS, the SOM and clustering as complementary methods
that provide representations of the same reality from different analytical points of view. ... This approach may be complemented with other kinds of representation based on network analysis.
that provide representations of the same reality from different analytical points of view. ... This approach may be complemented with other kinds of representation based on network analysis.
Within the techniques of multivariate statistical analysis, three basic methods are included (Egghe and Rousseau, 1990):
1) cluster analysis,
2) principal component analysis (PCA), and
3) multidimensional scaling (MDS).
1) cluster analysis,
2) principal component analysis (PCA), and
3) multidimensional scaling (MDS).
These methods are referred to as dimensionality-reduction methods because this function is to simplify what might at first appear to be a complex pattern of associations among many entities (Kinnucan, 1987).
SOM is based on the principle of the self-organization and grouping of n-dimensional vectors in a bidimensional space, and has been used to reduce dimensions in a wide variety of document spaces of diverse nature. ... According to Kaski (1997), the SOM presents four important properties for data exploration:
1) Ordered display. The characteristic help us to understand the underlying structures in the series of data.
2) Visualization of clusters. We are able to perceive the clustering density of the different regions of the map.
3) Missing data.
4) Outlier. This enables us to detect unusual cases caused by input errors or similar anomalies.
Journal co-citation mapping is potentially of interest both to the researcher studying the structure of scholarly specialities through the published literature and to the collection manager concerned with developing core journals lists, selecting journals and evaluating collections that serve particular research-oriented constituencies McCain(1991).
The main difference is that the SOM tries to present a locally corrected projection, whereas MDS attempts to preserve all the distances between the points. That is, MDS is distance preserving, while the SOM is topology-preserving.
Tijssen (1993) said that the mental representations of the experts, on an individual micro-level, and the bibliometric maps, on a macro-level, are inherently different.
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