出版社 | MarketsandMarkets |
出版年月 | 2025年1月 |
Knowledge Graph Market – Global Forecast to 2030
The construction of intelligent knowledge graphs through AI is expected to change how organizations deal with large datasets. The effort of human intervention is drastically reduced when it comes to identifying and extricating relationships between different data points. The automation includes the processes carried out by most types of AI-driven tools such as natural language processing (NLP), machine learning algorithms, etc., to automatically interpret, unstructured or structured data, identify relevant patterns, and correlate such relevant information. This automation speeds up the construction of the graphs and at the same time increases accuracy, ensuring that the relationships represented in it are as relevant and up to date as possible to an end user.
AI によるインテリジェントなナレッジ グラフの構築により、組織が大規模なデータセットを扱う方法が変わると予想されます。異なるデータポイント間の関係を特定して抽出する場合、人的介入の労力が大幅に軽減されます。自動化には、自然言語処理 (NLP) や機械学習アルゴリズムなど、ほとんどのタイプの AI 駆動ツールによって実行されるプロセスが含まれており、非構造化データまたは構造化データを自動的に解釈し、関連するパターンを特定し、関連情報を関連付けます。この自動化により、グラフの構築が高速化されると同時に精度が向上し、グラフ内で表される関係がエンド ユーザーにとって可能な限り関連性があり、最新のものになることが保証されます。

The major players in the Knowledge Graph market include IBM Corporation (US), Oracle (US), Microsoft Corporation (US), AWS (US), Neo4j (US), Progress Software (US), TigerGraph (US), Stardog (US), Franz Inc (US), Ontotext (Bulgaria), Openlink Software (US), Graphwise (US), Altair (US), Bitnine ( South Korea) ArangoDB (US), Fluree (US), Memgraph (UK), Datavid (UK), and SAP (Germany), GraphBase (Australia), Metaphacts (Germany), Relational AI (US), Wisecube (US), Smabbler (Poland), Onlim (Austria), Graphaware (UK), Diffbot (US), Eccenca (Germany), Conversight (US), , Semantic Web Company (Austria), ESRI (US). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches, enhancements, and acquisitions to expand their Knowledge Graph market footprint.
The report provides insights on the following pointers:
Analysis of key drivers (rising demand for AI/generative AI solutions, rapid growth in data volume and complexity, growing demand for semantic search), restraints (data quality and Integration challenges, scalability Issues) opportunities (data unification and rapid proliferation of knowledge graphs, increasing adoption in healthcare and life sciences), and challenges (lack of expertise and awareness, standardization and interoperability) influencing the growth of the Knowledge Graph market.
- Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the Knowledge Graph market.
- Market Development: The report provides comprehensive information about lucrative markets and analyses the Knowledge Graph market across various regions.
- Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the Knowledge Graph market.
Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading include include IBM Corporation (US), Oracle (US), Microsoft Corporation (US), AWS (US), Neo4j (US), Progress Software (US), TigerGraph (US), Stardog (US), Franz Inc (US), Ontotext (Bulgaria), Openlink Software (US), Graphwise (US), Altair (US), Bitnine ( South Korea) ArangoDB (US), Fluree (US), Memgraph (UK), GraphBase (Australia), Metaphacts (Germany), Relational AI (US), Wisecube (US), Smabbler (Poland), Onlim (Austria), Graphaware (UK), Diffbot (US), Eccenca (Germany), Conversight (US), , Semantic Web Company (Austria), ESRI (US), Datavid (UK), and SAP (Germany).