Personal computing vs. personal computers

Most discussion of personal computers in organizations focuses on a peripheral issue: the choice between distributed computer hardware and central computer hardware — between personal computers and mainframes. The real issue has nothing to do with personal computers or other hardware; it is the difference between organizational computing and personal computing in organizational information systems. This paper discusses the differences between organizational computing and personal computing, the connections between the organizational and the personal computing systems within organizations, and the role of MIS.     

基于隐含语义的个性化信息检索

随着互连网上信息资源的极度膨胀，出现了各种各样的信息搜集工具给用户提供信息服务，但是目前的信息搜集系统在给用户提供信息服务时，很难根据用户的个人信息实现个性化的信息服务，不同的用户相同的查询请求，返回的查询结果是相同的，这给用户的使用带来了很大的不便，而隐含语义检索(LSI)可以利用关键词之间的语义信息完成信息的搜索。提出了利用LSI来进行个性化信息检索算法的几种实现方法，并通过实验验证了算法的有效性。     

Phymail Box: an information appliance that checks and prints only important emails

Phymail Box is an information appliance that checks and prints important emails according to the user’s preferences. It allows people to manage the email experience in a new way, making it easier and more pleasant to use than other available systems     

Disability digital divide: the use of the internet,smartphones, computers and tablets among people with disabilities in Sweden

Although Sweden is one of the most digitalized countries and the Swedish population’s use of the internet is among the most studied in the world, little is known about how Swedes with disabilities use internet. The purpose of this study is to describe use of and perceived difficulties in use of the internet among people with disabilities and to explore digital divides in-between and within disability groups, and in comparison with the general population. This is a cross-sectional survey targeting the same issues as other nationwide surveys but adapted for people with cognitive disabilities. Participants were recruited from May to October 2017 by adaptive snowball sampling. The survey comprised questions on access to and use of devices, and use of and perceived difficulties in use of internet. A total of 771 people responded to the survey, representing 35 diagnoses/impairments. Larger proportions of people with autism, ADHD and bipolar disorder reported using internet than other disability groups. Women with autism used the internet more than any other disability group, and women with aphasia used the internet the least. People with disabilities related to language and understanding reported more difficulties using internet than other disability groups. Larger proportions of participants than the general Swedish population reported not feeling digitally included. In many but not all disability groups, larger proportions of men than women reported not feeling digitally included. Our findings show that there are differences in digital inclusion between sub-groups of diagnoses/impairments. Thus, disability digital divides are preferably investigated by sub-grouping disabilities, rather than studied as one homogeneous group.

     

Personal assistants: Direct manipulation vs. mixed initiative interfaces

Interface agents are computer programmes that provide assistance to users dealing with computer-based applications. The introduction of agents to user interfaces caused the exploration of new metaphors to enhance user ability to directly manipulate interfaces. In this regard, mixed-initiative interaction refers to a flexible interaction strategy in which agents contribute with users by providing suitable information at the most appropriate time. Mixed-initiative approaches promise to dramatically enhance human–computer interaction by allowing agents to resemble human assistants. In this paper, we report a study on how the interaction metaphor can affect the user perception of agent capabilities and, in turn, the final success of agents.     

Privacy vs. information technology

Modern information technology is facilitating the steady disappearance of individual privacy - even under normal circumstances. Add a real or hyped threat to the common good, and the erosion of individual privacy is further accelerated.     

Social reactions toward people vs. computers: How mere lables shape interactions

What criteria afford a machine the status of a social agent? In this investigation, the mere label identifying an oral interviewer as human or computer was sufficient to affect participants’ responses toward the interviewer during an online interview for a competitive mock job. Participants’ impressions of the interviewer and self-reported emotional reactions to the interview were unaffected by the interviewer’s identity. Despite this invariance, however, participants exhibited more interpersonal displays when the interviewer was identified as human. Overall, these results show that participants engaged in heightened impression management strategies (deferral to, or attempts to engage or appease) with the “human” interviewer. The computer interviewer did not merit equivalent social status.     

Speech information retrieval: a review

Speech is an information-rich component of multimedia. Information can be extracted from a speech signal in a number of different ways, and thus there are several well-established speech signal analysis research fields. These fields include speech recognition, speaker recognition, event detection, and fingerprinting. The information that can be extracted from tools and methods developed in these fields can greatly enhance multimedia systems. In this paper, we present the current state of research in each of the major speech analysis fields. The goal is to introduce enough background for someone new in the field to quickly gain high-level understanding and to provide direction for further study.     

Banks and information technology: marketability vs. relationships

This paper evaluates the impact of information technology (IT) on the operations of banks and the structure of the banking industry, including implications for stability. On the one hand, banks can focus on relationship banking and use IT developments to tailor services to individual needs and build enhanced, albeit modified, relationships with customers. On the other hand, IT better allows banks to exploit economies of scale and scope, which are most evident in transaction banking. Another manifestation of IT is via financial innovations that have enhanced marketability. Stability enters the picture because increased marketability facilitates opportunistic behavior. Together with enhanced herding behavior and changes in industry structure, this could undermine stability and augment systemic risk, calling for a regulatory overhaul.     

HINMINE: heterogeneous information network mining with information retrieval heuristics

The paper presents an approach to mining heterogeneous information networks by decomposing them into homogeneous networks. The proposed HINMINE methodology is based on previous work that classifies nodes in a heterogeneous network in two steps. In the first step the heterogeneous network is decomposed into one or more homogeneous networks using different connecting nodes. We improve this step by using new methods inspired by weighting of bag-of-words vectors mostly used in information retrieval. The methods assign larger weights to nodes which are more informative and characteristic for a specific class of nodes. In the second step, the resulting homogeneous networks are used to classify data either by network propositionalization or label propagation. We propose an adaptation of the label propagation algorithm to handle imbalanced data and test several classification algorithms in propositionalization. The new methodology is tested on three data sets with different properties. For each data set, we perform a series of experiments and compare different heuristics used in the first step of the methodology. We also use different classifiers which can be used in the second step of the methodology when performing network propositionalization. Our results show that HINMINE, using different network decomposition methods, can significantly improve the performance of the resulting classifiers, and also that using a modified label propagation algorithm is beneficial when the data set is imbalanced.     

On the performance of COBOL programs in large vs. mini computers

The comparative performance characteristics of COBOL programs in a small versus large computer systems are investigated. The vehicle consists of a set of synthetic benchmark COBOL programs, each measuring a particular aspect of COBOL computations, data manipulation, and input/output is made on both a large scale computer (IBM 370/158) and a minicomputer (Texas Instruments TI980). Results of a number of such experiments are presented and comparisons made between results obtained from the two systems.     

CI-SNF: Exploiting contextual information to improve SNF based information retrieval

Similarity networks contain important topological features and patterns critical to understanding interactions among samples in a large dataset. To create a comprehensive view of the interactions within a dataset, the Similarity Network Fusion (SNF) technique has been proposed to fuse the similarity networks based on different data types into one similarity network that represents the full spectrum of underlying data. In this paper, a modified version of SNF, which is named as Contextual Information based SNF (CI-SNF), is proposed. In CI-SNF, first, modified Jaccard distance is performed on the SNF fused similarity to utilize the contextual information contained in the fused similarity network. Second, the local consistency of samples from the same category is enhanced by speculating that the samples which are located high in the Jaccard distance based ranking list of a specific query are from the same category as the query. Third, the inverted index technique is introduced to utilize the sparsity property of the locally consistent similarity network to enhance the computational efficiency. To verify the effectiveness and efficiency of CI-SNF model, it is applied in four different tasks, Cover Song Identification (CSI), image classification, cancer subtype identification, and drug taxonomy, respectively. Extensive experiments on thirteen challenging datasets demonstrate that CI-SNF scheme outperforms state-of-the-art similarity fusion algorithms including SNF in all four tasks. It is also verified that utilizing the contextual information contained in the SNF-based similarity network helps to enhance the performance of the SNF-based scheme, further.     

SAPHIRE--an information retrieval system featuring concept matching, automatic indexing, probabilistic retrieval, and hierarchical relationships

SAPHIRE (Semantic and Probabilistic Heuristic Information Retrieval Environment) is an experimental computer program designed to test new techniques in automated information retrieval in the biomedical domain. A main feature of the program is a concept-finding algorithm that processes free text to find canonical concepts. The algorithm is designed to handle a wide variety of synonyms and convert them to canonical form. This allows natural language to be used for query input and also serves as the basis for a new approach to automatic indexing based on a combination of probabilistic and linguistic methods.