Recommendation of startups as technology cooperation candidates from the perspectives of similarity and potential: A deep learning approach

Kim, Hyoung Jun; Kim, Tae San; Sohn, So Young

doi:10.1016/j.dss.2019.113229

Cited by 32 publications

(27 citation statements)

References 42 publications

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“…Hence, recommender approaches related to startup projects have received increasing consideration. ey can be beneficial for youth entrepreneurship and increase the country's economic benefits [47]. e majority of proposed recommendation approaches in the startup field use the CF, the CB, or hybrid methods [48].…”

Section: Recommendations For Smart City Service Startupsmentioning

confidence: 99%

“…To rank the startups and recommend them to investment companies, Xu et al [49] used collected data about investment companies, startup projects, and investment events. Kim et al [47] suggested a framework that recommends expected startups to enterprises based on their technological similarity scores between patent abstracts and startup profile texts by collecting patent applications from the WISDOMAIN website and startup information from "Crunchbase" database. Zhong et al [50] proposed an integrated approach to recommend a startup investment to investors by studying the investor's investment preferences and the expected returns and potential risks of the startup.…”

Section: Recommendations For Smart City Service Startupsmentioning

confidence: 99%

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Intelligent Recommendations of Startup Projects in Smart Cities and Smart Health Using Social Media Mining

Karâa

Alkhammash

Slimani

et al. 2021

Journal of Healthcare Engineering

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The paper presents a recommendation model for developing new smart city and smart health projects. The objective is to provide recommendations to citizens about smart city and smart health startups to improve entrepreneurship and leadership. These recommendations may lead to the country’s advancement and the improvement of national income and reduce unemployment. This work focuses on designing and implementing an approach for processing and analyzing tweets inclosing data related to smart city and smart health startups and providing recommended projects as well as their required skills and competencies. This approach is based on tweets mining through a machine learning method, the Word2Vec algorithm, combined with a recommendation technique conducted via an ontology-based method. This approach allows discovering the relevant startup projects in the context of smart cities and makes links to the needed skills and competencies of users. A system was implemented to validate this approach. The attained performance metrics related to precision, recall, and F-measure are, respectively, 95%, 66%, and 79%, showing that the results are very encouraging.

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Section: Recommendations For Smart City Service Startupsmentioning

confidence: 99%

Section: Recommendations For Smart City Service Startupsmentioning

confidence: 99%

Intelligent Recommendations of Startup Projects in Smart Cities and Smart Health Using Social Media Mining

Karâa

Alkhammash

Slimani

et al. 2021

Journal of Healthcare Engineering

View full text Add to dashboard Cite

show abstract

“…Technological similarity is generally conceived as the similarity between the properties of particular technologies that firms actively utilize [12]. It can be determined by measuring the degree of overlap between technological documents such as patents held by each firm [13], and the degree of overlap can be measured by calculating the distance between feature vectors extracted from the patent documents [14], [15]. Doc2vec, an extension of word2vec, has been used in recent years for converting textual information into feature vectors [16].…”

Section: A Peer Group For Technology Evaluationmentioning

confidence: 99%

A Hybrid Approach to Building Peer Groups for Technology Evaluation to Generate Reference Information

Seo

2021

IEEE Access

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“…The advanced technologies adopted bring significant benefits to companies along with innovation [ 28 , 29 ] and induce the interest of investors and governments [ 30 ]. However, the fluctuating technology market makes it impossible for a company to perform all its tasks using its internal R&D alone [ 22 ]. Subcontractors can solve this problem by working as partners to their prime contractors in the technology market.…”

Section: Literature Reviewmentioning

confidence: 99%

“…As subcontracting is known as a governance which is efficient for the diffusion of new technology [ 21 ], subcontractors need to innovate, gain technological competitiveness, and cooperate with their prime contractors actively in a win-win relationship by investing in technologies and resources. It would be difficult for subcontractors to keep pace with the new technology demands and rapidly changing trends by themselves [ 22 ]. On the other hand, the risk can be reduced as subcontractors grow along the direction of their prime contractors.…”

Section: Introductionmentioning

confidence: 99%

Recommending blue ocean technologies for subcontractors: A framework based on business reports of prime contractors and patents

2021

Self Cite

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Subcontractors depend heavily on their prime contractor and thus find it very risky to enter a new business on their own. This study proposes a framework for these subcontractors to develop blue ocean technologies related to their prime contractor. First, the primary technologies predicted to be promising are extracted from the business reports of the prime contractor. Sub-technologies are then selected through a patent-based search using keywords and International Patent Classification codes of the primary technologies. From them, blue ocean technologies are proposed by optimizing the weighted mean of the min-max normalized market value, degree of competition in the technology market, and subcontractors’ potential technological capabilities for each sub-technology. This study shows that subcontractors can enhance their technology competitiveness by finding a low-risk blue ocean technology. Our empirical research on the subcontractors of a semiconductor firm identified technological patent fields for them to pursue. From our framework, subcontractors can identify blue ocean technologies by considering their prime contractor’s future industrial areas and technologies of interest as well as their own technological capabilities. Furthermore, the prime contractors can gain the synergy effect of technology expansion through cooperation.

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Recommendation of startups as technology cooperation candidates from the perspectives of similarity and potential: A deep learning approach

Cited by 32 publications

References 42 publications

Intelligent Recommendations of Startup Projects in Smart Cities and Smart Health Using Social Media Mining

Intelligent Recommendations of Startup Projects in Smart Cities and Smart Health Using Social Media Mining

A Hybrid Approach to Building Peer Groups for Technology Evaluation to Generate Reference Information

Recommending blue ocean technologies for subcontractors: A framework based on business reports of prime contractors and patents

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